Improved biomarkers for predicting progression to active tuberculosis (TB) are urgently needed, especially in people with HIV, who are at elevated risk. We used high-throughput plasma proteomics and machine learning to identify signatures associated ...
BACKGROUND: To evaluate the precision of automated segmentation facilitated by deep learning (DL) and dose calculation in adaptive radiotherapy (ART) for nasopharyngeal cancer (NPC), leveraging synthetic CT (sCT) images derived from cone-beam CT (CBC...
BACKGROUND: Intra-aortic balloon pump (IABP) implantation in the perioperative period of cardiac surgery is an auxiliary treatment for cardiogenic shock. However, there is a lack of effective prediction models for preoperative IABP implantation.
BACKGROUND: Suicide represents a significant challenge to public health that calls for a suitable intervention from the healthcare sector. Despite the typically low suicide rate among most Muslim nations, research indicates that there is an increase ...
BACKGROUND: The Anemia Control Model (ACM) is a decision support system powered by an artificial intelligence core designed to assist nephrologists in managing anemia therapy for in-center hemodialysis (HD) patients. This study aims to evaluate the c...
This paper presents a novel system for optimizing Tai Chi movement training using computer vision and deep learning technologies. We developed a comprehensive framework incorporating multi-view pose estimation, temporal feature extraction, and real-t...
The purpose of this pilot study was to test an adapted childhood obesity prevention intervention called Preventing Obesity Using Digital-Assisted Movement and Eating (ProudMe) in under-resourced schools. Six schools were cluster-randomized to ProudMe...
Sleep apnea, a prevalent respiratory disorder, poses significant health risks, including cardiovascular complications and behavioral issues, if left untreated. Traditional diagnostic methods like polysomnography, although effective, are often expensi...
Clinical trials demonstrate that screening can reduce lung cancer mortality by over 20%. However, lung cancer screening effectiveness (reduction in lung cancer specific mortality) may vary by personal risk-factors. Here we evaluate heterogeneity in l...
OBJECTIVES: This study aims to detect characteristic fundus changes in pathological myopia using deep learning (DL)-based analysis of ultra-widefield (UWF) fundus imaging.
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