The United States is facing a convergence of health care pressures. There is a surge in chronic diseases, with most individuals aged 65 years or older having multiple chronic conditions. There is also ...

Several health systems are tackling higher volumes with command centers, and at a seven-hospital system based in Philadelphia, a capacity ...

Exploring the Role of Virtual Reality and Metaverse in Treating Mental Health: Operating Models and Challenges in Adoption ...

Abstract Healthcare workers are the backbone of resilient health systems, yet in many African countries they operate under extreme occupational stress, inadequate training, poor working conditions, ...

Abstract: Clinical predictive analysis is a crucial task with numerous applications and has been extensively studied using machine learning approaches. Clinical notes, a vital data source, have been ...

Introduction The use of digitally enabled technology is considered a promising platform to prevent morbidity and enhance youth mental health as youth are growing up in the digital world and accessing ...

Introduction SLE is a chronic autoimmune disease characterised by multisystem involvement and fluctuating clinical course, ...

Abstract: Data imbalance is a fundamental challenge in applying language models to biomedical applications, particularly in ICD code prediction tasks where label and demographic distributions are ...

Background: Large language models (LLMs) offer promise for enhancing clinical care by automating documentation, supporting decision-making, and improving communication. However, their integration into ...

UpToDate—the popular clinical research and information database used by thousands of hospitals around the globe—has officially tacked on an AI solution. As one family physician put it, who currently ...

This is the official PyTorch implementation of LLMDet. Recent open-vocabulary detectors achieve promising performance with abundant region-level annotated data. In this work, we show that an ...

Large language models (LLMs) have demonstrated remarkable versatility in oncology applications, such as cancer staging and survival analysis. Despite their potential, ethical concerns such as data ...