Shoulder impingement syndrome (SIS) is a prevalent musculoskeletal condition requiring effective preventive strategies. This study introduces a comprehensive approach to SIS prevention through smart physical activity monitoring. Wearable sensors, inc...
This study aimed to evaluate diffuse large B-cell lymphoma (DLBCL) patients who have refractory/relapsed disease and characterize the heterogeneity of DLBCL using patient-level radiomics analysis based on F-FDG PET/CT. A total of 132 patients diagnos...
Proposed methods for prostate cancer screening are currently prohibitively expensive (due to the high costs of imaging equipment such as magnetic resonance imaging and traditional ultrasound systems), inadequate in their detection rates, require high...
The gut microbiota is profoundly influenced by dietary choices, with emerging evidence linking it to various health outcomes. Here, we investigate diet-microbiota associations using detailed temporal nutrition intake data captured through real-time f...
Healthcare rationing is unavoidable in systems constrained by limited resources. While decisions about who should be treated are ethically complex, they must reflect not only efficiency concerns but also socially accepted values. This study aims to d...
Decisions regarding veno-venous extracorporeal membrane oxygenation (vv-ECMO) in patients with acute respiratory distress syndrome (ARDS) are often based solely on clinical and physiological parameters, which may insufficiently reflect severity and h...
This study presents a novel deep learning (DL) framework, the Deep Neural Frailty Competing Risks (DNFCR) model, which simultaneously integrates frailty and competing risks (CR) for mortality prediction in heart failure (HF). While existing models li...
Prostate cancer remains a leading cause of mortality, necessitating precise histopathological segmentation for accurate Gleason Grade assessment. However, existing deep learning-based segmentation models lack contextual awareness and explainability, ...
While delays in human-robot encounters can harm perceptions of competence, they can also enhance engagement and relatability, making timing a crucial factor in the design of robot behaviors for effective human-robot interaction. Previous research has...
The rapid advancement of artificial intelligence, particularly large language models like ChatGPT-3.5, presents promising applications in healthcare. This study evaluates ChatGPT-3.5's validity in responding to post-operative patient inquiries follow...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.