Long-term electrocardiogram (ECG) has become one of the important diagnostic assist methods in clinical cardiovascular domain. ECG is primarily used for detection various diseases that are caused by cardiac arrhythmia such as myocardial infarction, cardiomyopathy, and myocarditis. In past few years, development an automatic heartbeat classification method been a challenge. With accumulation medical data, personalized patient possible. For long-term data method, holter, it difficult to obtain...

This study examines the impact of social engagement on elderly health in China. A two-stage residual inclusion (2SRI) regression approach was used to examine causal relationship. Our dataset comprises 9253 people aged 60 or above from China Health and Retirement Longitudinal Survey (CHARLS) conducted 2011 2013. Social significantly improved self-rated reduced mental distress, but had no effect chronic disease status. Compared with rural areas, played a more important role promoting status...

Maintaining sustained attention during a prolonged cognitive task often comes at cost: high levels of mental fatigue. Heuristically, fatigue refers to feeling tiredness or exhaustion, and disengagement from the hand; it manifests as impaired behavioral performance. In order effectively reduce undesirable yet preventable consequences in many real-world workspaces, better understanding underlying neural mechanisms is needed, continuous efforts have been devoted this topic. comparison with...

Background The coronavirus disease (COVID-19) has become an urgent and serious global public health crisis. Community engagement is the first line of defense in fight against infectious diseases, general practitioners (GPs) play important role it. GPs are facing unique challenges from disasters pandemics delivering care. However, there still no suitable mobile management system that can help collect data, dynamically assess risks, effectively triage or follow-up with patients COVID-19....

In recent years, an increasing number of people have become concerned about their health. Most chronic diseases are related to lifestyle, and daily activity records can be used as important indicator Specifically, using advanced technology automatically monitor actual activities effectively prevent manage diseases. The data in this paper were obtained from acceleration sensors gyroscopes integrated smartphones. We designed efficient Adaboost-Stump running on a smartphone classify five common...

Pancreas identification and segmentation is an essential task in the diagnosis prognosis of pancreas disease. Although deep neural networks have been widely applied abdominal organ segmentation, it still challenging for small organs (e.g. pancreas) that present low contrast, highly flexible anatomical structure relatively region. In recent years, coarse-to-fine methods improved accuracy by using coarse predictions fine stage, but only object location utilized rich image context neglected....

Non-used clinical information has negative implications on healthcare quality. Clinicians pay priority attention to relevant their specialties during routine practices but may be insensitive or less concerned about showing disease risks beyond specialties, resulting in delayed and missed diagnoses improper management. In this study, we introduced an electronic health record (EHR)-oriented knowledge graph system efficiently utilize non-used buried EHRs. EHR data were transformed into a...

Accurate and timely core body temperature measurement is essential for identifying preventing heat-related illnesses. Infrared thermography (IRT) provides a non-invasive, full-scale efficient path screening. However, the complexity of environmental factors personal features continuously affect measured skin temperature, resulting in low accuracy reliability existing monitoring by IRT. To address this issue, study proposed an innovative prediction model (CTPM) IRT based on heat transfer...

Abstract Background Colon cancer is common worldwide and the leading cause of cancer-related death. Multiple levels omics data are available due to development sequencing technologies. In this study, we proposed an integrative prognostic model for colon based on integration clinical multi-omics data. Methods total, 344 patients were included in study. Clinical, gene expression, DNA methylation miRNA expression retrieved from The Cancer Genome Atlas (TCGA). To accommodate high dimensionality...

Background: The objectives of this study were to develop a 3D convolutional deep learning framework (CarotidNet) for fully automatic segmentation carotid bifurcations in computed tomography angiography (CTA) images and facilitate the quantification stenosis risk assessment stroke. Methods: Our pipeline was two-stage cascade network that included localization phase phase. based on version U-Net, but refined three ways: (I) by adding residual connections supervision strategy cope with...

Objective: The present study focused on examining fear of the coronavirus disease 2019 (COVID-19) is correlated with depression and explored potential role resilience social support association between COVID-19 (FoC) among Chinese outbound students studying online in China amid pandemic period. Methods: A total 476 from different universities worldwide, currently via mode China, completed an survey including measures FoC, resilience, support, depression. Results: (1) Fear was positively...

Abstract The article offers a survey of currently notable artificial intelligence methods (released between 2019-2023), with particular emphasis on the latest advancements in detecting rheumatoid arthritis (RA) at an early stage, providing treatment, and managing disease. We discussed challenges these areas followed by specific (AI) techniques summarized advances, relevant strengths, obstacles. Overall, application AI fields RA has potential to enable healthcare professionals detect earlier...

Abstract We present a new post processing method of simulating depth field based on accurate calculations circles confusion. Compared to previous work, our derives actual scene information directly from the existing buffer, requires no specialized rendering passes, and allows easy integration into applications. Our implementation uses an adaptive, two‐pass filter, producing high quality effect that can be executed entirely GPU, taking advantage parallelism modern graphics cards permitting...

Uncertainty is mushrooming throughout COVID-19, and intolerance of uncertainty (IoU) nudges people into mental health difficulties involving fear, depression, anxiety. The objective this study was to investigate the role depression fear COVID-19 (FoC) in association between IoU future career anxiety (FCA) among Chinese university students during pandemic. This involved 1,919 undergraduate from 11 universities eight cities with an online self-administered survey that included demographic...

At present, most clinical data are exchanged between organizations within a regional system. However, people traveling abroad may need to visit hospital, which would make international exchange of very useful.Since 2007, collaborative effort achieve sharing has been carried out at Zhejiang University in China and Kyoto Miyazaki Japan; each is running information center. Methods An layer system named Global Dolphin was constructed with several key services, patients' health countries using...