Technology and Health Care

CT images are often affected by blooming artifacts during the diagnosis that facilitate an overestimation of the expression of calcification stenosis, thereby impeding the accurate diagnosis of this condition.

Arterial calcification can act as a blooming artifact in computed tomography (CT) images, leading to overestimations of the blood vessel and the size of calcified plaque. This study proposes an improved CT post-processing method that accurately measures calcium and lumen size in blood vessels.

Six hundred and thirty calcium datasets were obtained from 63 patients diagnosed with a vascular disease. Patients were grouped into three sets corresponding to each image acquisition method used: G1, for the invasive coronary angiography (ICA); G2, for multiplanar reconstruction (MPR) imaging and post-processing; and G3, for the novel method of mixed Gaussian filter and K-mean clustering (GK). Results of GK were generated by adding Gaussian and k-mean clustering algorithms to the MPR post-processing procedure. The analysis of variance (ANOVA), linear regression, and intraclass correlation coefficient (ICC) were used to compare the accuracy and sensitivity of the different methods. All measurements were performed multiple times to mitigate human error.

The ANOVA test revealed no significant differences between the G1 and G3 groups. Hence, linear regression was used to analyze the correlation between the G1 and G3 groups ( p < 0.05, R2 = 0.885), and a higher correlation than G1 and G2 was reported ( p > 0.05, R2 = 0.432). ICC was performed for reproducibility, wherein high correlation was identified among all groups.

Results of the study indicate that the GK method yields images that are very similar to ICA image measurements. This suggests that the GK can be used as a more effective post-processing method over the inaccurate MPR while remaining non-intrusive when determining the arterial stenosis degree, unlike the ICA.

The coherent plane wave compounding (CPWC) is a promising technique to enhance the imaging quality while maintaining the high frame rate in the plane wave ultrasound imaging. Recently, the spatial-coherence-based method has been specially designed to process echo matrix required by the minimum variance (MV) method.

In this paper, a novel beamforming method that integrates the submatrix-spatial-coherence-based MV with the sign coherence factor (SCF) is proposed to further improve the imaging quality.

The submatrix smoothing technique is modified to smooth and de-correlate signals of the receiving array dimension. Then, the SCF is used to modify the input vector of the beamformer, which can reduce side lobe noises with almost no increase in the amount of calculation. Simulation, phantom, in vivo, and sound velocity error experiments have been performed to verify the superiority of the proposed beamformer.

The imaging results show that the proposed approach performs better in the imaging resolution and contrast compared to the traditional CPWC method.

The robustness of the proposed method is enhanced, and the over-suppression phenomenon can be alleviated, which is a phenomenon that occurs in the original spatial-coherence and SCF methods.

Knowledge regarding the hypothalamic nuclei is essential for understanding neuroanatomy and has substantial clinical relevance.

The aim was to contribute to elucidate the complex hypothalamic architecture for research and provide an anatomical basis for clinical brain operation.

In this research, high-resolution and true-color sectioned images from Visible Korean were employed for hypothalamic nuclei and neighboring structures surface modeling, and a high-resolution three-dimensional atlas of the hypothalamus was created.

Surface models of 26 structures including the hypothalamic nuclei and its neighboring structures were produced, which contained 5 anterior hypothalamic areas’ nuclei, 4 intermediate hypothalamic areas’ nuclei, 3 lateral hypothalamic areas’ nuclei, and 2 posterior hypothalamic areas’ nuclei, as well as 12 hypothalamic neighboring structures.

The study evaluated the topographical anatomy of the hypothalamic nuclei and its neighboring structures based on true-color and highresolution sectioned images of Visible Korean.

According to statistics of the Ministry of Health and Welfare in 2017, the second leading cause of death in Taiwan was lung cancer.

Routine treatment planning does not consider photoneutron dose equivalent (PNDE) of patient induced secondary radiation resulting from primary exposure of lung cancer. However, such treatment is potentially important for improving estimates of health risks.

This study used 10, 30, 50, 70, and 90 kg of polymethylmethacrylate (PMMA) phantoms as patient to measure PNDE varying anatomical area during lung cancer of intensity modulated radiotherapy (IMRT) treatment. Paired thermoluminescent dosimeters (TLD-600 and 700) were calibrated using university reactor neutrons. TLDs were inserted into phantom which was closely corresponded of the represented tissues or organs.

Neutron doses (ND) of organ or tissue ( N ⁢ D T ) were determined in these phantoms using paired TLDs approach. The risks of incurring fatal secondary malignancies, maximum statistical and total errors were estimated. Evaluated PNDE ranged from 0.80 ± 0.12 to 0.56 ± 0.08 mSv/Gy for these phantoms.

The estimated N ⁢ D T decreased with increasing distance that is from the central axis. Evaluated PNDE and N ⁢ D 𝑠𝑘𝑖𝑛 for these phantoms were discussed. This investigation also identified secondary risks associated with PNDE relating to radiation protection.

Automated diagnosis of gastrointestinal stromal tumors’ (GISTs) cancerization is an effective way to improve the clinical diagnostic accuracy and reduce possible risks of biopsy. Although deep convolutional neural networks (DCNNs) have proven to be very effective in many image classification problems, there is still a lack of studies on endoscopic ultrasound (EUS) images of GISTs. It remains a substantial challenge mainly due to the data distribution bias of multi-center images, the significant inter-class similarity and intra-class variation, and the insufficiency of training data.

The study aims to classify GISTs into higher-risk and lower-risk categories.

Firstly, a novel multi-scale image normalization block is designed to perform same-size and same-resolution resizing on the input data in a parallel manner. A dilated mask is used to obtain a more accurate interested region. Then, we construct a multi-way feature extraction and fusion block to extract distinguishable features. A ResNet-50 model built based on transfer learning is utilized as a powerful feature extractor for tumors’ textural features. The tumor size features and the patient demographic features are also extracted respectively. Finally, a robust XGBoost classifier is trained on all features.

Experimental results show that our proposed method achieves the AUC score of 0.844, which is superior to the clinical diagnosis performance.

Therefore, the results have provided a solid baseline to encourage further researches in this field.

Ticks are known as the representatives of hematophagous arachnids. They cause various tick-borne diseases, such as severe fever with thrombocytopenia syndrome (SFTS) and Lyme disease. To understand the mechanism of virus infection caused by ticks, morphology for the anatomical characteristics of crucial organs has been widely studied in acarological fields. The conventional methods used for tick observation have inevitable limitations. Dissection is the standard method to obtain the morphological information, and complex microscopy methods were utilized alternatively.

The study goal is to obtain the morphological information of ticks in different growth stages non-invasively.

Optical coherence tomography (OCT) is employed to acquire structural images of various internal organs without damage for observing the growth process of larva, nymph, and adult in Haemaphysalis longicornis ticks in real-time.

Various internal organs, such as salivary glands, rectal sac, genital aperture, and anus, were well-visualized by the OCT enface and cross-sectional images, and the variation in size of these organs in each growth stage was compared quantitatively.

Based on the obtained results, we confirmed the potential feasibility of OCT as a non-destructive real-time tool for morphological studies in acarology. Further research using OCT for acarological applications can include monitoring the growth process of ticks in terms of structural changes and investigating morphological differences between normal and virus-infected tick specimens.

The etiology of polycystic ovary syndrome (PCOS) remains unclear with highly heterogeneous clinical manifestations, recently growing evidence revealing genetic variants play a crucial part in its pathogenesis.

This study aimed to examine the correlation between SNPs in miRNA-135a’s binding site of targeted gene IRS2 and clinical manifestations of PCOS in Chinese females.

A total of 126 Chinese women with PCOS and 109 healthy women were enrolled, divided into 4 groups based on different clinical features of hyperandrogenemia (HA), insulin resistance (IR), polycystic ovary morphology (PCOM) and obesity. We analyzed 2 single nucleotide polymorphisms (SNPs) of the IRS2 gene (rs2289046 and rs1865434) and clinical features’ laboratory measurements such as sex hormone, fasting plasma glucose (FPG), fasting plasma insulin (FINS).

Located in miRNA-135a binding site of IRS2 gene, the rs2289046’s triple genotypes distribution showed a significant difference between PCOS/control group and PCOM/non-PCOM group ( P < 0.05) while the rs1865434’s triple genotype distribution showed a significant difference between obesity/non-obesity group ( P < 0.05).

The results revealed the two SNPs as rs2289046 and rs1865434 in the IRS-2 binding region of miRNA-135a have correlations with the clinical features of PCOS in Chinese population.

Classifying T1-weighted Magnetic Resonance brain scans into cerebrospinal fluid, gray matter and white matter is one of the most critical tasks in neurodegenerative disease analysis. Since manual delineation is a labor-intensive and time-consuming process, automated methods have been widely adopted for this purpose. One group of commonly used method by biomedical researchers are based on Gaussian mixture model. The main drawbacks of this model include complex computational cost and parameter selection with the presence of imaging defects such as intensity inhomogeneity and noise.

To alleviate these aspects, an improved Gaussian mixture model-based method is proposed in this work.

Standard mixture model was used to formulate individual voxel intensity. A set of spatial weightings were created to represent local tissue characteristics. The emphasis of this method is its “lite” and robust implementation mode highlighted by a dedicated entropy term. The Expectation-Maximization algorithm was then iteratively executed to estimate model parameters. The Maximum a Posteriori criterion was employed to determine for each voxel if it belongs to a certain tissue.

The proposed method was validated on both simulated and real MR scans. The averaged Dice coefficient of segmented brain tissues on each dataset ranged between [66.41, 87.42] for cerebrospinal fluid, [80.57, 85.35] for gray matter, and [83.17, 85.63] for white matter.

Experiments illustrated the effectiveness and reliability in tissue classification against imaging defects compared with manually constructed reference standard.

Radiologists widely use the minimum detectable difference (MDD) concept for inspecting the imaging quality and quantify the spatial resolution of scans.

This study adopted Taguchi’s dynamic algorithm to optimize the MDD of cardiac CT angiography (CTA) using a V-shaped line gauge and three PMMA phantoms (50, 70, and 90 kg).

The phantoms were customized in compliance with the ICRU-48 report, whereas the V-shaped line gauge was indigenous to solidify the cardiac CTA scan image quality by two adjacent peaks along the V-shaped slit. Accordingly, the six factors A-F assigned in this study were A (kVp), B (mAs), C (CT pitch), D (FOV), E (iDose), and F (reconstruction filter). Since each factor could have two or three levels, eighteen groups of factor combinations were organized according to Taguchi’s dynamic algorithm. Three welltrained radiologists ranked the CTA scan images three times for three different phantoms. Thus, 27 (3 × 3 × 3) ranked scores were summed and averaged to imply the integrated performance of one specific group, and eventually, 18 groups of CTA scan images were analyzed. The unique signal-to-noise ratio (S/N, dB) and sensitivity in the dynamic algorithm were calculated to reveal the true contribution of assigned factors and clarify the situation in routine CTA diagnosis.

Minimizing the cross-interactions among factors, the optimal factor combination was found to be as follows: A (100 kVp), B (600 mAs), C (pitch 0.200 mm), D (FOV 280 mm), E (iDose 5), and F (filter XCA). The respective MDD values were 2.15, 2.32, and 1.87 mm for 50, 70, and 90 kg phantoms, respectively. The MDD of the 90 kg phantom had the most precise spatial resolution, while that of the 70 kg phantom was the worst.

The Taguchi static and dynamic optimization algorithms were compared, and the latter’s superiority was substantiated.

The results of urine tests are often affected by improper midstream urine collection time, urine spilling, and urine pollution, all of which can lead to an increase in the test error.

To solve this problem, aiming at improving the toilet environment at the hospitals and public physical examination centers, this paper designs an automatic urine collection system. It can automatically adjust the position of the urine cup with an infrared remote controller, or manually, adjust the position of the urine cup in special situations according to the needs of the user. It also has an alarm function.

The overall size and shape are designed based on the squatting pan, suitable for disposable plastic urine cups of different shapes and sizes. It can realize the automatic collection of midstream urine, manual collection in exceptional cases, emergency stops, and rescue calls.

Through the trial survey, there was a significant difference between the statistical results of using the device and not using the device ( t = 13.937, P = 0.000). 96% of the subjects thought that the design of the system was reasonable, 22% thought that it was inconvenient to use, and 91.7% of the medical staff thought that the system met the sampling requirements.

Therefore, the trial evaluation is satisfactory, and the proposed collection system is suitable for use in hospitals at all levels and public health examination centers with a large amount of inspection.

Quantitative measures of the finger tapping task is important for objective assessment of bradykinesia. However, age-related changes in quantitative measures are still unclear.

The aim of this study was to quantitatively investigate age-related group differences in finger tapping performance.

Eighty-three healthy normal subjects with age ranging from aged 20 to 89 years participated in this study. All subjects were instructed to tap their index finger and thumbs as rapidly as possible and with as large amplitude as possible. Angular velocity of the finger tapping movement was measured using a gyrosensor. Quantitative variables include root mean squared (RMS) angular velocity, RMS angular displacement, peak power and peak frequency derived from angular velocity signals.

Significant age-related differences were observed in RMS angular velocity, peak power and peak frequency ( P < 0.001). Specifically, the oldest age group had the slowest average speed, the lowest peak power and peak frequency. These results indicate deterioration in finger speed, intensity of the main movement component and tapping frequency due to aging.

The results suggest that the quantitative variables should be adjusted for age when clinicians assess Parkinsonian bradykinesia. The results contribute to the development of an accurate and quantitative assessment tool for bradykinesia.

Radiotherapy plays an important role in cancer treatment today. Successful radiotherapy includes precise positioning and accurate dosimetry.

To use NIPAM gel dosimeter and concentric swing machine to simulate and evaluate the feasibility of lung or upper abdominal tumor dose distribution during breathing.

We used a concentric swing machine to simulate actual radiotherapy for lung or upper abdomen tumors. A 4 × 4 cm 2 irradiation field area was set and MRI was performed. Next, readout analysis was performed using MATLAB and the 3 mm, 3% gamma passing rate > 95% was used as a basis for evaluation.

The concentric dynamic dose curve for a simulated respiratory rate of 3 seconds/breath and 4 × 4 cm 2 field was compared with 4 × 4, 3 × 3, and 2 × 2 cm 2 treatment planning systems (TPS), and the 3 mm, 3% gamma passing rate was 42.87%, 54.96%, and 49.92%, respectively. Pre-simulation showed that the high-dose region dose curve was similar to the 2 × 2 cm 2 TPS result. After appropriate selection and comparison, we found that the 3 mm, 3% gamma passing rate was 97.92% on comparing the > 60% dose curve with the 2 × 2 cm 2 TPS.

NIPAM gel dosimeter and concentric swing machine use is feasible to simulate dose distribution during breathing and results conforming to clinical evaluation standards.

Chronic obstructive pulmonary disease (COPD) causes chronic obstructive conditions, chronic bronchitis, and emphysema, and is a major cause of death worldwide. Although several efforts for identifying biomarkers and pathways have been made, specific causal COPD mechanism remains unknown.

This study combined biological interaction data with gene expression data for a better understanding of the biological process and network module for COPD.

Using a sparse network-based method, we selected 49 genes from peripheral blood mononuclear cell expression data of 136 subjects, including 42 ex-smoking controls and 94 subjects with COPD.

These 49 genes might influence biological processes and molecular functions related to COPD. For example, our result suggests that FoxO signaling may contribute to the atrophy of COPD peripheral muscle tissues via oxidative stress.

Our approach enhances the existing understanding of COPD disease pathogenesis and predicts new genetic markers and pathways that may influence COPD pathogenesis.

Acne vulgaris is one of the most prevalent skin conditions, which harms not only the patients’ physiological conditions, but also their mental health. Early diagnosis and accurate continuous self-monitoring could help control and alleviate their discomfort.

We focus on the development and comparison of deep learning models for locating acne lesions on facial images, thus making estimations on the acne severity on faces via medical criterion.

Different from most existing literature on facial acne analysis, the considered models in this study are object detection models with convolutional neural network (CNN) as backbone and has better interpretability. Thus, they produce more credible results of acne detection and facial acne severity evaluation.

Experiments with real data validate the effectiveness of these models. The highest mean average precision (mAP) is 0.536 on an open source dataset. Corresponding error of acne lesion counting can be as low as 0.43 ± 6.65 on this dataset.

The presented models have been released to public via deployed as a freely accessible WeChat applet service, which provides continuous out-of-hospital self-monitoring to patients. This also aids the dermatologists to track the progress of this disease and to assess the effectiveness of treatment.

The mechanism of prevention and treatment of epilepsy is a hot issue in theoretical research.

In this paper, we studied the control mechanism of the generalized spike-and-wave discharges (GSWD) by different types of external electrical stimulation acting on the subthalamic nucleus (STN) in a computational model.

Firstly, we analyzed the pathological mechanism of seizures, which were induced by different parameters in the thalamocortical (TC) circuit. Then, a voltage V was exerted in the STN. At last, we used the sine wave and square wave current stimulation in the STN.

We found that seizures can be inhibited by tuning stimulus intensity into suitable range, and the direction of adjustment depended on the size of the parameter. We observed that the seizure can also be inhibited by tuning different parameters in current.

Different inhibition mechanisms can be explained in this model, which may provide theoretical evidences for selecting the optimal treatment scheme in the clinical.

Ultrasound computed tomography (USCT) is a promising technique for improving the detection of breast cancer. Image quality of USCT has a major impact on the breast cancer diagnosis.

This paper investigates the combination of variational mode decomposition (VMD) and coherent factor method for USCT image quality enhancement.

The signals can be decomposed into multiple intrinsic mode functions (IMFs) sifting through the frequency by VMD method. Refactoring the remaining IMFs, spatio-temporally smoothed coherence factor (STSCF) beamforming method is applied to reconstructed data for USCT.

The validation of combination the VMD and STSCF is described through the breast phantom experiment and in vivo experiments. The evaluation indicators such as contrast ratio (CR), contrast to noise ratio (CNR) and signal to noise ratio (SNR) have been better improved in the experimental results. For the breast phantom, the proposed method gives a higher resolution and the better contrast properties for the hyperechoic cyst. The borders of cysts and tumors in the breast phantom can be distinguished clearly. For volunteer breast experiments, artifacts are removed more efficiently while the clutters are suppressed simultaneously.

The combination of VMD and STSCF can further reduce the noise and suppress the side lobes.

Breast cancer has long been one of the major global life-threatening illnesses among women. Surgery and adjuvant therapy, coupled with early detection, could save many lives. This underscores the importance of mammography, a cost-effective and accurate method for early detection. Due to the poor contrast, noise and artifacts which results in difficulty for radiologists to diagnose, Computer-Aided Diagnosis (CAD) systems are hence developed. The extraction of breast region is a fundamental and crucial preparation step for further development of CAD systems.

The proposed method aims to extract breast region accurately from mammographic images where noise is suppressed, contrast is enhanced and pectoral muscle region is removed.

This paper presents a new deep learning-based breast region extraction method that combines pre-processing methods containing noise suppression using median filter, contrast enhancement using CLAHE and semantic segmentation using Deeplab v3 + model.

The method is trained and evaluated on mini-MIAS dataset. It has also been evaluated on INbreast dataset. The results outperform those generated by other recent researches and are indicative of the capacity of the model to retain its accuracy and runtime advantage across different databases with different image resolutions.

The proposed method shows state-of-the-art performance at extracting breast region from mammographic images. Wide range of evaluation on two commonly used mammography datasets proves the ability and adaptability of the method.

It has been found that baicalin have anti-inflammatory effects since it reduces the elevated levels of pro-inflammatory cytokines. Meanwhile, it has also been shown that baicalin brings positive effects against rheumatoid arthritis (RA). However, little is observed on its beneficial effects on adjuvant arthritis.

To consider the anti-inflammatory influence of baicalin on adjuvant arthritis rats and its related autophagy mechanism.

In this research, there are six groups of rats, each has 10 rats in it. These groups are normal group (normal saline), model group (normal saline), dexamethasone group (0.125 mg/kg dexamethasone), low-dose baicalin group (50 mg/kg baicalin), medium-dose baicalin group (100 mg/kg baicalin) and high-dose baicalin group (200 mg/kg baicalin). The degrees of adjuvant-induced swelling in rats’ feet were measured every 4 days and the arthritis scores were calculated every 7 days. The inflamed joint tissues were taken after rats were sacrificed. The rat’ joints showed pathological changes, which were observed by HE staining. The relative expression levels of inflammatory factors IL-6, IL-1, IL-17, TNF- α , COX2, and COX1 in the rats’ snovial tissues were detected by RT-PCR. As for the expression levels of autophagy markers Beclin1, Atg5, Atg7, Atg12, microtubule-associated protein-light chain3-II (LC3-II), Bcl-2, and Bax in the synovial tissue, they were discoverd by Western blot.

Baicalin could significantly inhibit the inflammatory response of adjuvant arthritis rats.

RT-PCR studies showed that the different doses of baicalin could inhibit the expression of TNF-a, IL-6, IL-1, IL-17, COX2 and COX1 in the synovial tissue ( P < 0.05 or P < 0.01). Western blot studies showed that the different doses of baicalin could reduce the expression of Atg5, Atg7, Atg12, LC3-II, Beclin1 and Bcl-2 proteins, and increase the expression of Bax proteins in the synovial tissue.

In endoscopic photoacoustic tomography (EPAT), the photoacoustically induced ultrasonic wave reflects at tissue boundaries due to the acoustic inhomogeneity of the imaged tissue, resulting in reflection artifacts (RAs) in the reconstructed images.

To suppress RAs in EPAT image reconstruction for improving the image quality.

A method was presented to render the cross-sectional images of the optical absorption with reduced RAs from acoustic measurements. The ideal photoacoustic signal was recovered from acoustic signals collected by the detector through solving a least square problem. Then, high-quality images of the optical absorption distribution were reconstructed from the ideal signal.

The results demonstrated the improvement in the quality of the images rendered by this method in comparison with the conventional back-projection (BP) reconstructions. Compared with the short lag spatial coherence (SLSC) method, the peak signal-to-noise ratio (PSNR), normalized mean square absolute distance (NMSAD), and structural similarity (SSIM) were improved by up to 8%, 20%, and 5%, respectively.

This method was capable of rendering images displaying the complex tissue types with reduced RAs and lower computational burden in comparison with previously developed methods.

HER2 gene expression is one of the main reference indicators for breast cancer detection and treatment, and it is also an important target for tumor targeted therapy drug selection. Therefore, the correct detection and evaluation of HER2 gene expression has important value for clinical treatment of breast cancer.

The study goal is to better classify HER2 images.

For general convolution neural network, with the increase of network layers, over fitting phenomenon is often very serious, which requires setting the value of random descent ratio, and parameter adjustment is often time-consuming and laborious, so this paper uses residual network, with the increase of network layer, the accuracy will not be reduced.

In this paper, a HER2 image classification algorithm based on improved residual network is proposed. Experimental results show that the proposed HER2 network has high accuracy in breast cancer assessment.

Taking HER2 images in Stanford University database as experimental data, the accuracy of HER2 image automatic classification is improved through experiments. This method will help to reduce the detection intensity and improve the accuracy of HER2 image classification.

Patients with unexplained pneumonia appeared in Wuhan, Hubei Province at the end of 2019.

To analyze the clinical data of patients with severe COVID-19.

Medical records of 28 severe patients admitted to the intensive care unit of Wuhan Xinzhou District People’s Hospital were collected from January 31 to March 17.

The mortality rate of severe patients in our study was 39.3%. There were statistically significant differences in age, admission systolic blood pressure, lymphocyte count, albumin, total bilirubin, and lactate dehydrogenase between the death group and the survival group ( P < 0.05). There were statistically significant differences in APACHE II, CURB-65, SOFA, respiratory frequency, systolic pressure, platelet, procalcitonin, albumin, creatinine, creatine kinase isoenzyme, lactate dehydrogenase, chloride ion, prothrombin time, international normalized ratio, arterial partial pressure of oxygen, and FiO2 at ICU between the death group and the survival group ( P < 0.05).

Fever and cough are the main symptoms, which is useful for predicting the prognosis to dynamically measure the APACHE II, CURB-65, SOFA, respiratory frequency, lymphocyte count, platelet, lactate dehydrogenase, and coagulation tests. The drugs that protect the liver and heart may improve the survival rate of patients with severe COVID-19.

As an essential indicator of labour and delivery, uterine contraction (UC) can be detected by manual palpation, external tocodynamometry and internal uterine pressure catheter. However, these methods are not applicable for long-term monitoring.

This paper aims to recognize UCs with electrohysterogram (EHG) and find the best electrode combination with fewer electrodes.

112 EHG recordings were collected by our bespoke device in our study. Thirteen features were extracted from EHG segments of UC and non-UC. Four classifiers of the decision tree, support vector machine (SVM), artificial neural network, and convolutional neural network were established to identify UCs. The optimal classifier among them was determined by comparing their classification results. The optimal classifier was applied to evaluate all the possible electrode combinations with one to eight electrodes.

The results showed that SVM achieved the best classification capability. With SVM, the combination of electrodes on the right part of the uterine fundus and around the uterine body’s median axis achieved the overall best performance.

The optimal electrode combination with fewer electrodes was confirmed to improve the clinical application for long-term monitoring of UCs.

Compared to benchtop ultrasound machines, mobile ultrasound machines require portable batteries when acquiring information regarding human tissues during outdoor activities.

A novel fisheye lens type was designed to address the charging issue where it is difficult to constantly track the sun. This method does not require the use of a mechanical motor that constantly tracks the sun to charge the portable batteries.

To obtain an optical solar power system, the numerical aperture (NA) and field angle must be increased. Therefore, we use the fisheye lens with the largest field angle.

The NA of the designed fisheye lens system reaches 0.75, allowing light collection of approximately ± 48 ∘ . Additionally, the efficiency ratio of the central and surrounding areas also satisfies more than 80% at a field angle of 85 ∘ and more than 70% at field angles of 85 ∘ to 90 ∘ , respectively.

We designed a novel fisheye lens for solar-powered mobile ultrasound machines used outdoors.

Although patients with frozen shoulders have the range of motion (ROM) of their shoulder’s abduction movements measured at hospital and the physical therapy visits, multiple visits to check for progress is often difficult. Thus, we developed an artificial intelligence-based image recognition detectable sensor (AIRDS) intended for easy use at home.

The purpose of this study was to determine the accuracy of a sensor (AIRDS) measuring shoulder abduction angle, thus offering a valid and feasible system for monitoring patients with frozen shoulder.

Ten patients with frozen shoulder (5 males, 5 females) performed shoulder joint movements while being measured with the AIRDS system and the 3-dimensional Vicon system. The measure of the outcome included the linear regression of the shoulder abduction joint kinematics.

Linear regression analysis of the AIRDS system and the Vicon system demonstrated a significant correlation coefficient of R 2 = 0.9979 ( P < 0.05).

Our results provide novel, promising evidence that AIRDS can accurately measure the timing and total spatial characteristics of clinical movements. AIRDS is designed to provide real-time ROM measurements for joint mobility using artificial intelligence instead of the judgement of the physical therapist.

Brain metastasis (BM) is one of the main causes of high morbidity and mortality in cancer patients.

To evaluate the factors that influenced the survival time of patients with primary cancer and survival time after BM.

Ninety patients with BM diagnosed by magnetic resonance imaging (MRI) were included in the study. We retrospectively analyzed the time to brain metastasis (TTB), overall survival time (OS1) and survival time after BM (OS2). The Kaplan-Meier method and Cox regression analysis were used for survival analyses.

The median TTB was 12.0 (95% CI: 9.2–14.8 months), the median OS1 was 31.0 (95% CI: 25.8–35.2 months) and the median OS2 was 14.0 (95% CI: 10.9–17.1 months). Surgical excision of the primary tumor was an independent factor for a prolonged TTB ( p < 0.000) and prolonged OS1 ( p < 0.000). A single intracranial metastatic lesion was an independent protective factor for prolonged OS1 ( p = 0.011) and prolonged OS2 ( p = 0.050). TTB, OS1 and OS2 were analyzed with Gender ( p < 0.000, < 0.000, and = 0.017, respectively).

It suggests that TTB can be prolonged by primary tumor resection. Furthermore, women with a prolonged TTB and single intracranial metastasis are associated with high OS. These were helpful for the clinical treatment of BM patients before brain metastasis.

Tongue inspection is vital in traditional Chinese medicine. Fissured tongue is an important feature in tongue diagnosis, and primarily corresponds to three Chinese medicine syndromes: syndrome-related hotness, blood deficiency, and insufficiency of the spleen. Diagnosis of the syndrome is significantly affected by the experience of clinicians, and it is difficult for young doctors to perform accurate diagnoses.

The syndrome not only depends on the local features based on fissured regions but also on the global features of the whole tongue; therefore, a syndrome diagnosis framework combining the global and local features of a fissured tongue image was developed in the present study to achieve a quantitative and objective diagnosis.

First, we detected the fissured region of a tongue image using a single-shot multibox detector. Second, we extracted the global and local features from a whole tongue image and a fissured region using TongueNet (developed in-house). Third, we developed a classifier to determine the final syndrome.

Based on an experiment involving 721 fissured tongue images, we discovered that TongueNet affords better feature extraction. The accuracy of TongueNet was 4% ( p < 0.05) and 3% ( p < 0.05) higher than that of InceptionV3 and ResNet18, respectively, for whole tongue images. Meanwhile, at local fissured regions, the accuracy of TongueNet was 3% ( p < 0.05) higher than that of InceptionV3 and equal to that of ResNet18. Finally, the fusion features outperformed the global and local features with a 78% accuracy.

Our findings indicate that TongueNet designed with batch normalization and dropout is more suitable for uncomplicated images than InceptionV3 and ResNet18. In addition, compared with the global features, the fusion features supplement the detailed information of the fissures and improve classification accuracy.

Gestational diabetes mellitus (GDM) is a metabolic disease that seriously endangers the health of mothers and children. It is important to monitor GDM in real-time before diagnosis and to prevent it effectively.

GDM was divided into the second trimester diagnosed diabetes mellitus (GDM_24) and the third trimester diagnosed diabetes mellitus (GDM_30). The risk prediction of two types of GDM was performed in normal pregnant women at 11–13 and 16–19 weeks of pregnancy, respectively.

By stages, the K-W test was used to analyze the differences between basic information and energy metabolism factors, and multiple logistic regression was used to analyze the risk of energy metabolism factors and to correct the confounders with significant differences.

For the GDM_24 group, each additional unit of oxygen consumption (VO 2 ), carbon dioxide production, and resting energy expenditure (REE) increased the risk by 2.4%, 3.5%, 0.4%, and 2.1%, 2.6%, and 0.3%, respectively, at 11–13 and 16–19 weeks of pregnancy. For the GDM_30 group, each additional unit of VO 2 and REE was associated with an increased risk of 2.3% and 0.3%, respectively, at 16–19 weeks of pregnancy.

The risk of GDM_30 only appeared in pregnant women during 16–19 weeks of pregnancy, which may indicate that GDM_24 and GDM_30 have different pathogenesis.

Alternative splicing is a mechanism to produce different proteins with diverse functions from one gene. Many splicing factors play an important role in cancer progression. PRPF8 is a core protein component of the spliceosome complex, U4/U6-U5 tri-snRNP.

However, PRPF8 involved in mRNA alternative splicing are rarely included in the prognosis.

We found that PRPF8 was expressed in all examined cancer types. Further analyses found that PRPF8 expression was significantly different between the breast cancer and paracancerous tissues.

Survival analyses showed that PRPF8-high patients had a poor prognosis, and the expression of PRPF8 is associated with distant metastasis-free survival (DMFS) and post progression survival (PPS). Gene Set Enrichment Analysis (GSEA) has revealed that PRPF8 expression is correlated with TGF- β , JAK-STAT, and cell cycle control pathways. Consistent with these results, upon PRPF8 silencing, the growth of MCF-7 cells was reduced, the ability of cell clone formation was weakened, and p ⁢ 21 expression was increased.

These results have revealed that PRPF8 is a significant factor for splicing in breast cancer progression.

With the continuous expansion of urban scale and the increasing concentration of population, public health crisis has become an important part of urban residents’ health management. The outbreak of the COVID-19 pandemic in Wuhan in 2020 has sounded the alarm.

With the government at all levels to carry out the construction of urban Internet of things and information internet, the Internet backbone network has been built, deployed a large number of sensors, and collected a large number of urban situation data.

In this paper, situational awareness technology is introduced into public health emergency services.

By constructing ontology, situational data and residents’ health data are integrated. Through key technologies such as situational data collection, data fusion and data mining, real-time perception of environmental conditions of public health emergency scene is realized, and situational data fusion and situational information reasoning model are constructed.

The model is applied to the public health crisis emergency simulation system to verify the effectiveness of the model.

High installation and operating cost have limited applications for many circumstances. In practice, primary and shielding coils cannot insert into the magnet pole simultaneously owing to deficient workspace for the planar permanent MRI systems

To minimize eddy currents induced in the resist-eddy current plates and pole piece when the gradient coil current switches on and off rapidly.

A theoretical framework that have minimum power dispassion and magnetic energy with eddy plate is proposed for a planar gradient coil. The mirror image of the magnetostatic model is substituted into the stream function for designing a minimum power dispassion planar gradient coil. A finite-difference is used to formulate the coil distribution that makes magnetic field similar to the required magnetic field for gradient coil design.

A coil designed with actively shielded was simulated and compared with the designed gradient coils using mirror image theory and piece pole effect. According to the numerical evaluation of the x and z coils, the operating currents in the cases were reduced to 34.4% using magnetostatic mirror-image method to replay the active shielding. Moreover, there was a significant improvement on the shielding effect when added to resistive eddy current plate.

Using the magnetostatic mirror image theory and mirror-image model, the current density function that could not only gives the minimum power dissipation and magnetic energy with the presence of the eddy plate and pole piece effect, but also provides excellent coil performance compared with active shielding solution.

The routine radiation therapy treatment planning does not include secondary radiation and peripheral doses resulting from radiotherapy exposure in patients with nasopharyngeal carcinoma (NPC) undergoing Volumetric Modulated Arc Therapy (VMAT) using an linear accelerator (linac) of Axesse (Elekta 2538).

VMAT has a better dose conformity of the tumor and is also operated by adjusting the shapes of mulileaf collimator. However, such treatment is potentially important to improve the accuracy of estimated health risks.

This study aimed to evaluate the equivalent dose of organ or tissue ( D T ) and effective dose ( E ) for normal organs using the Alderson Rando phantom as an equivalent of the human body. Thermoluminescent dosimeters (TLD-100H) were calibrated by 6 MV X-ray originated by the linac. A total of 252 TLDs were used. These TLDs were inserted into phantom organ or tissue which closely approximated to these places.

The thyroid dose ( D 𝑡ℎ𝑦 ) had the highest dose, 1840 ± 202 mSv/treatment. The E of the Rando was 7.11 ± 0.61 mSv/treatment, as estimated using ICRP 103. The skin doses ( D 𝑠𝑘𝑖𝑛 ) varied significantly outside the treatment field and decreased as the distance from the treatment field increased.

This study can be referred to practical guidance regarding radiation protections of the public.

The occurrence and development of caries is a complex process affected by multiple factor.

The present study was envisaged to evaluate the plaque fluid in caries free children and children with high caries, in order to establish a data set of bacterial secretion proteomics. A non-labeled quantitative technique based on two-dimensional liquid chromatography-series mass spectroscopy was employed to detect plaque fluid. Based on the proteomics data, the database search, data processing and pathway analysis illuminated the function of these proteins, and clarified the role of plaque microecology in caries occurrence and development.

The study enrolled 8 caries free (CF) children, whose decayed-missed-filled surface of teeth is 0 (dmfs = 0), and caries sensitive (CS) children, whose decayed-missed-filled surface of teeth is > 10(dmfs > 10) (3 ∼ 5 years old) for the smooth tooth plaque and the plaque in the high caries group. The plaque protein was extracted using the unlabeled quantitative technique like liquid chromatography-series mass spectrometry, using DeCyder TM MS Differential Analysis Software (version 1.0, GE Healthcare) that detected and compared the spectra, and quantified the full scanning before series mass spectroscopy. After obtaining all peptides with quantitative information, significantly differential polypeptide molecules were obtained ( p < 0.05), and a metabolic pathway analysis was performed.

We identified 1,804 peptides with quantitative information, including 39 in CF, 30 in CS, and 1,735 similarly expressing peptides. After statistical analysis, 603 statistically different expression peptide data sets were obtained, including 202 high-expressed peptides in Group CF, 33 greater than 1.5 fold peptides, 401 high-expressed in Group CS and 199 greater than 1.5 fold peptide (173 nonredundant proteins).

Our study obtained the largest known dataset of the bacterial secretion protein in children with high caries, and screened the data set of high caries state. 603 peptides were statistically rich in 101 pathways, including glycolysis pyruvate acid metabolism, tricarboxylic acid cycle, pentyl phosphate pathway, fructose mannose metabolism, starch and sucrose metabolism, and ABC transporters.

Hydroxyapatite bioceramic is a kind of bone implant commonly used in oral clinic treatment. In the early stage of tissue repair, cells will suffer hypoxic due to the interruption of blood supply.

Studying the expression of osteoblasts in hypoxic environment will help us to understand the expression and response mechanism of osteoblasts at the implantation site of hydroxyapatite in the early stage of hypoxia.

MG63 osteoblast cell line was used in this study. The cells of normal group were incubated under normal oxygen and hydroxyapatite ceramics condition. The cells of hypoxia group were incubated under hypoxia (37 ∘ C, 8% CO 2 , 8% O 2 , 86% N 2 ) and hydroxyapatite ceramics condition. Cell proliferation was measured by CCK8 assay. Apoptosis was measured by flow cytometry. Serum alkaline phosphatase (ALP) activity was measured by ALP kit. Hypoxia inducible factor (HIF- α ) and vascular endothelial growth factor (VEGF) were detected by Western blot.

Compared to the normal group, the cells of hypoxia group showed a dramatically higher proliferation ability, especially at 48 h ( P < 0.05). Due to hypoxia, cell apoptosis was induced, but there is no difference between these two groups. Interestingly, the ALP activity of hypoxia group was higher than that of normal group at 24 h and 48 h ( P < 0.05). Mechanically, western blot result showed that the protein level of both HIF- α and VEGF were up-regulated in hypoxia group.

Under hypoxia condition, hydroxyapatite bioceramics can promote the proliferation of MG63 osteoblasts, elevate the activity of alkaline phosphatase and upregulate HIF- α and VEGF expression without effect on apoptosis.

Children with Down syndrome (DS) have critical biomechanical impairments such as increased ligamentous laxity, muscle hypotonia, and dysfunctional motor coordination, which makes performing everyday tasks challenging.

The purpose of the study was to explore the differences in the vertical joint stiffness, plantar force, and range of motion during drop landing for DS and age-matched typically developing children.

Six young male children with DS and age-matched seven healthy typically developing children (TD) assessed joint strength using an isokinetic dynamometer and performed five trials of single-leg drop jump using force platform and motion capture system.

The peak vertical ground reaction force (VGRF), Range of motion (ROM), joint stiffness, and joint strength of lower limb were calculated and compared across DS and TD groups. The results revealed a significantly larger peak VGRF [ z = - 2.857, p < 0.001] values for the DS group compared to the TD groups. The results of Spearman’s correlation analysis showed a negative correlation between hip joint stiffness and knee joint ROM [ r = - 0.886, p < 0.05] and ankle joint stiffness and knee joint ROM [ r = - 0.829, p < 0.05] for DS.

The abnormal movements observed among DS was not due to the difference in stiffness of the lower extremity but due to the utilization of different landing mechanisms with changes in ROM.

The imaging photoplethysmography (IPPG) technology has been demonstrated to be an effective method for heart rate (HR) monitoring. However, some interference caused by the ambient illumination variation and facial motion severely influences the accuracy of the HR measurement. Some color spaces and color formats are assumed to reduce the interference, and enhance the accuracy of HR estimation.

The aim is to identify the optimal color space and format for IPPG based HR measurement.

Six color spaces and 3 color formats are compared in this study, based on an IPPG based HR measurement system. 424 pieces of videos captured by the system are used for the selection of the optimal color channel and color space; while 10 pieces of videos are for the identification of the optimal color format.

The results shows that the green channel of RGB space is the optimal color channel, and RGB is the optimal color space, in respect of the mean squared error of HR estimation. BayerBG 8bit is found to be the optimal color format for video recording, which can significantly reduce the HR estimation error.

BayerBG 8bit color format for video recording, and RGB color space for video analysis is suggested for the IPPG based HR measurement system. The suitable configuration of color space and format could enhance the accuracy of HR measurement.

There are few studies on the differences in clinical outcomes with implant guides made by different methods in cases with a single tooth loss and adjacent tooth support

To compare the use of digital and traditional implant guides in patients whose first molars are absent and who are undergoing implant restoration.

This study included 42 patients with first molars missing who were randomly divided into two groups: the digital group ( n = 21) and the control group ( n = 21). A CAD/CAM digital implant guide was used in the digital group, whereas a traditional impression was used in the control group. Then, the labor time, the intraoral fit of the implant guide, and the deviation of the screw access channel position were compared between the two groups.

The impression time and implant surgery time in the digital group were less than in the traditional group. The intraoral first fit of the guide in the digital group was higher than in the control group ( P < 0.05). The one-time satisfaction rate of the digital group was 100%, while five cases in the control group needed to be redone. In the digital group, there was no significant difference in the deviation of the screw access channel position between implants on the left and right sides. In the control group, the deviation of the screw access channel position on the right side was significantly lower than on the left side. Overall, the deviation of the screw access channel position was significantly lower in the digital group than in the control group.

In a first molar implant, the digital implant guide can effectively reduce the clinical operative time and the screw access deviation and improve efficiency. The clinical results with the digital guide provide a basis for its use in implant therapy for single missing teeth.

The gel dosimeter is a chemical as well as a relative dosimeter.

To evaluate the feasibility of using N-isopropylacrylamide (NIPAM) gel dosimeter to observe the dynamic dose effects and quantification of the respiration, and to help determine the safety margins.

The NIPAM gel dosimeter combined with the dynamic phantom was used to simulate radiotherapy of lung or upper abdominal tumor. The field set to 4 × 5 cm 2 , simulate respiratory rate of 4 sec/cycle, and motion range 2 cm. MRI was used for reading, and MATLAB was used for analysis. The 3%/3 mm gamma passing rate > 95% was used as a clinical basis for evaluation.

The dynamic dose curve was compared with 4 × 5, 4 × 4, 4 × 3 cm 2 TPS, and gamma passing rates were 74.32%, 54.83%, 30.18%. Gamma mapping demonstrated that the highest dose region was similar to the result of the 4 × 4 cm 2 TPS. After appropriate selection and comparing that the ⩾ 60% part of the dose curve with TPS, the gamma passing rate was 96.49%.

Using the NIPAM gel dosimeter with dynamic phantom to simulate organ motion during respiration for dynamic dose measurement and quantified the dynamic dose effect is feasible. The results are consistent with clinical evaluation standards.

Yes-associated protein (YAP) has been reported to act as a candidate human oncogene and played a critical role in the development of multiple cancer types.

We aimed to investigate the expression, function, and underlying mechanisms of YAP in gastric cancer (GC).

Expression levels of YAP in gastric tissues were tested. CCK8 assay, clonogenic assay, apoptosis assay, transwell assay, cell scratch assay and animal study were conducted to explore the function of YAP. Chromatin immunoprecipitation (ChIP) assay and luciferase reporter assay were performed to explore the underlying mechanism. Survival analysis was carried out to reveal the relationship between YAP and clinical outcome.

YAP was upregulated in gastric cancer tissues and correlates with poor prognosis. YAP could promote GC cells proliferation, metastatic capacity, inhibit GC cells apoptosis in vitro and in vivo. Both β -catenin and YAP were mainly localized withi the tumor cell nuclei. β -catenincould upregulate YAP expression by binding to the promotor region of YAP. Patients with both YAP and β -catenin negetive expression had a better prognosis than others.

YAP overexpression is driven by aberrant Wnt β -catenin signalingand then contributed to the GC tumorigenesis and progression. Thus, YAP might be a potential target for GC treatment.

Infant care activities can induce musculoskeletal disease. However, little is known about the biomechanical joint load during lifting-up of an infant.

The aim of this study was to investigate normalized maximum moment during lifting-up of infant dummies weighing 4.6 kg, 7.6 kg, and 9.8 kg.

Six healthy young subjects participated in our study. All subjects performed lifting-up activities of dummies to shoulder height with their feet apart and natural postures in their comfortable speed. Three-dimensional reflective marker trajectories and ground reaction forces were used as input to calculate joint moments using a full body musculoskeletal model. Joint moments were normalized by each subject’s body mass. Friedman’s test was performed to compare mean differences of normalized joint moments for lifting up three dummy weights.

Lumbar joint had the greatest normalized joint moment. Lumbar and hip extension moments were significantly increased with dummy weight ( P < 0.05). In contrast, knee extension and ankle plantarflexion moment were not significantly affected by dummy weight ( P > 0.05).

These results indicate that the lumbar joint plays the most important role in infant lifting-up motion and that the load of lumbar and hip joint should be reduced when lifting a heavier infant. These results could contribute to the development of an effective lifting strategy and an assisting device for lifting an infant.

Targeted therapy using anti-TNF (tumor necrosis factor) is the first option for patients with rheumatoid arthritis (RA). Anti-TNF therapy, however, does not lead to meaningful clinical improvement in many RA patients. To predict which patients will not benefit from anti-TNF therapy, clinical tests should be performed prior to treatment beginning.

Although various efforts have been made to identify biomarkers and pathways that may be helpful to predict the response to anti-TNF treatment, gaps remain in clinical use due to the low predictive power of the selected biomarkers.

In this paper, we used a network-based computational method to identify the select the predictive biomarkers to guide the treatment of RA patients.

We select 69 genes from peripheral blood expression data from 46 subjects using a sparse network-based method. The result shows that the selected 69 genes might influence biological processes and molecular functions related to the treatment.

Our approach advances the predictive power of anti-TNF therapy response and provides new genetic markers and pathways that may influence the treatment.

Video-assisted thoracic surgery (VATS) is a minimally invasive technique for the diagnosis and management of small pulmonary nodular lesions However, the identification of some lung nodules remains difficult.

This research aimed to investigate the clinical value of preoperative computed tomography (CT)-guided hookwire localization of solitary pulmonary nodules (SPNs) for thoracoscopic resection.

Seventy-one patients with 74 SPNs underwent VATS wedge resection after CT-guided hookwire localization. The mean diameter of the SPNs was 8.50 ± 4.53 mm,,besides, the mean distance from the SPNs to the parietal pleura was 16.81 ± 5.23 mm.

Sixty-nine of the 74 nodules were successfully localized using a CT-guided hookwire. The success rate of CT-guided localization was 93.2%. The average localization time was 15.23 ± 7.21 min per lesion. Seven patients (9.5%) had asymptomatic pneumothorax and 10 (13.5%) had minimal needle tract parenchymal hemorrhages after localization no clinical intervention was required for these patients. The rate of success for VATS wedge resection of the SPNs was 100%. Histological analysis of the SPNs revealed malignant disease in 67.4% of the patients.

Preoperative CT-guided hookwire localization for thoracoscopic resection is a safe and effective operation for the identification and stable fixation of SPNs.

Spatial disorientation (SD) is a problem that pilots often encounter during a flight. One reason for this problem is that among the three types of SD, there is no validated method to detect the Type I (unrecognized) SD.

In this pursuit, initially we reviewed the problems and the evaluation methods of associated with SD. Subsequently, we discussed the advantages and disadvantages of the subjective questionnaire evaluation method and the behavior evaluation method.

On the basis of these analyses, we proposed a method to detect the unrecognized SD that improved the assessment of SD to a significant extent. We developed a new direction to study the unrecognized SD based on the subjective report and the center of pressure (CoP).

The proposed evaluation method can assist the pilots to understand the feelings and physical changes, when exposed to unrecognized SD.

We hope that this evaluation method can provide a strong support in developing a countermeasure against the unrecognized SD and fundamentally solve the severe flight accidents arising due to them.

In the last 40 years, the number of deaths due to cancer has been the highest in Taiwan

To optimize the readout system of the thermoluminescent dosimeter (TLD)-100H, the radiation rates among the Tomotherapy (TOMO) facility of the Department of Radiology Oncology of Chung Shan Medical University Hospital (CSMUH) were calculated with a 3 2 full factorial design (FFD).

A ten-month survey of the facility was employed using the sensitive and accurate TLD method. The TLD system was optimized for maximum temperature, heat rate, and preheat temperature of Harshaw 3500 reader. Eight analyzed groups with different factors were tested.

The TOMO facility had significantly different radiation rates. The farther away from the gantry head, environmental radiation rates. The half value layer (HVL) was also determined. These results were compared with published. No significant contributions of environmental gamma radiations were detected except in the treatment room.

Those were far below the occupational doses recommended by ICRP 60.

Prediction of the depth of anesthesia is a difficult job in the biomedical field.

This study aimed to build a boosting-based prediction model to predict the depth of anesthesia based on four clinical monitoring data.

Boosting is a framework algorithm that is used to train a series of weak learners into strong learners by assigning different weights according to their classification accuracy. The input of the boosting-based prediction model included four types of clinical monitoring data: electromyography, end-tidal carbon dioxide partial pressure, remifentanil dosage, and flow rate. The output was the depth of anesthesia.

The boosting framework model built in this study achieved higher prediction accuracy and a lower discrete degree in predicting the depth of anesthesia compared with the DT-, KNN-, and SVM-based models.

The boosting framework was used to set up a prediction model to predict the depth of anesthesia based on four clinical monitoring data. In the experiments, the boosting framework model of this study achieved higher prediction accuracy and a lower discrete degree. This model will be useful in predicting the depth of anesthesia.

The beamforming algorithm is key to the image quality of the medical ultrasound system. The generalized sidelobe canceler (GSC) beamforming can improve the image quality in lateral resolution, but the contrast is not improved correspondingly.

In our research, we try to optimize the generalized sidelobe canceler to obtain images that achieve an improvement in both lateral resolution and contrast.

We put forward a new beamforming algorithm which combines the generalized sidelobe canceler and Eigenspace-Wiener postfilter. According to eigenspace decomposition of the covariance matrix of the received data, the components of the Wiener postfilter can be calculated from the signal matrix and the noise matrix. Then, the adaptive weight vector of GSC is further constrained by the Eigenspace-Wiener postfilter, which make the output energy of the receiving array closer to the desired signal than the conventional GSC output.

We compare the new beamforming algorithm with delay-and-sum (DS) beamforming, synthetic aperture (SA) beamforming, and GSC beamforming using the simulated and experimental data sets. The quantitative results show that our method reduces the FWHM by 85.5%, 80.5%, and 38.9% while improving the CR by 123.6%, 47.7%, 84.4% on basis of DS, SA, and GSC beamforming, respectively.

The new beamforming algorithm can obviously improve the imaging quality of medical ultrasound imaging systems in both lateral resolution and contrast.

The limiters have been used to protect the ultrasound receivers because of the inherent characteristic of the transducers which are required to use the high voltage excitation to obtain the reasonable echo signal amplitudes.

Among the variety of the limiters, the performances of discharge voltage degradation from the limiters gradually deteriorate the whole ultrasound systems according to the applied voltages of the ultrasonic transducers. This could cause the ultrasound systems to be unreliable for the long-term operations, resulting in possibly breaking the receiver systems.

Designed limiters were evaluated with insertion loss, total harmonic distortion, and pulse-echo responses with the ultrasound transducer devices.

Designed new dual-resistor-diode limiters exhibited greater and faster suppression of the pulse width (1.15 V and 6.1 μ s) for high-voltage signals.

Our proposed dual-resistor-diode limiter could be one of the potential candidates for reliable ultrasound receiver system.

Neck pain is the most common symptom of cervical spondylosis.

To discuss the indications for conventional acupuncture therapy (CAT) and motion style acupuncture therapy (MSAT) combined with CAT in neck pain patients using data mining.

Seventy-six participants with neck pain were recruited and randomly divided into two paralleled groups. Participants in intervention group received two-course MSAT at Houxi (SI3) and CAT at local neck region, while the control group received CAT at neck only. Take the SF-36 score scale and pain pressure threshold (PPT) values as the raw data and use data-mining to evaluate the clinical effect of two treatments.

Both groups have the best effect after one-time and one-course treatment. The main factors influencing effect most are Role-Emotional (RE), Physical Functioning (PF) and Social Functioning (SF) in intervention group, while it transfers to General Health (GH), RE and SF in control group. To patients in intervention group who scores 41.70 to 68.70 in PF before treatment, MSAT can effectively improve the restriction of activities and play an analgesic effect; to patients in control group who score 56.09 to 66.09 in GH before treatment, CAT may have curative effect.

Both MSAT and CAT can improve the life-quality of neck pain patients. Patients with high general health status before treatment can choose CAT, while patients who score mild to moderate decline in physiological function can choose MSAT combined with CAT.

The diagnosis of benign and malignant menopausal endometrial lesions (MEL) is often misled by complicated clinical indicators and ultrasonographic parameters in actual clinical applications.

To investigate the performance of clinical indicators and ultrasonographic parameters in the diagnosis of MEL.

A cohort of 156 enrolled menopausal patients with MEL was divided into benign group (128 cases) and malignant group (28 cases). Two clinical indicators of patient age (PA), abnormal vaginal bleeding (AVB) and three transvaginal ultrasonography (TVS) parameters of endometrial thickness (ET), endometrial uneven echo (EUE) and endometrial blood flow signal (EBFS) were measured for the mathematical modelling. The performance of combined indicators and individual indicators were firstly compared, and then the optimized combined indicators was compared with corresponding individual indicators, respectively.

Our experiments verified that the mathematical modelling presented robust capabilities in the diagnosis of MEL with the sensitivity, specificity and AUC of 78.6%, 75.8% and 0.83 for combined indicators, and 75.0%, 81.3% and 0.85 for optimized combined indicators, respectively. The cut off thresholds of PA was 57.5 years, ET was 11.5 mm. Furthermore, the AVB presented the most important risk factor among the optimized indicators of PA, ET and AVB ( P < 0.05).

The combined indicators presented better performance in differentiating benign and malignant MEL and the AVB demonstrated the most capability for clinical applications.

Tibial plateau fracture is a common fracture encountered in the clinic.

This study determined the optimal timing and surgical approach for patients with tibial plateau fracture.

Fifty-two patients with complex tibial plateau fractures were treated in our hospital (the People’s Hospital of Zhongjiang County) between 2013 and 2015. These patients were recruited as participants in this study; all patients were randomly allocated into two groups of 26 patients each. Patients in Group 1 underwent single-incision, single-plate knee surgeries via an antero-lateral approach, and patients in Group 2 underwent anterior median incisions of the knee for double-plate surgeries. The effects of the approaches were compared and analyzed.

The best time to perform surgery was 6–8 days post-injury. The anterior median incision, double-plate method approach was better than the antero-lateral, single-incision, single-plate method. For the former method, the healing among middle-aged and young patients was better than that of elderly patients, and that healing of men was slightly better than that of female patients. However, the degree of healing among patients was > 80% at 5 months postoperatively. The purpose of surgical management has been fully achieved.

The optimal timing of surgery for patients with complex tibial plateau fractures is 6–8 days post-injury. The surgical approach needs to be determined based on the actual condition of the patient. However, the treatment effect of an anterior median incision, double-plate method is better, and the recovery rate may approach 80% at 5 months postoperatively.