Artificial intelligence (AI) holds great promise for analyzing complex data to advance patient care and disease research. For example, AI interpretation of retinal imaging may enable the development of noninvasive retinal biomarkers of systemic disea...
Unhealthy lifestyle behaviors are a doorway to downstream health consequences characterized by the following: 1) poor quality of life and diminished mobility; 2) increased likelihood of chronic disease risk factors and diagnoses; and, ultimately, 3) ...
INTRODUCTION: Following numerous mishaps and near-misses, the U.S. Naval Surface Force established the Operational Surface Risk Indicators (OSRI) project to explore a robust proactive risk analysis and reduction capability. The OSRI model leverages m...
AIMS: Numerous risk factors for the development of obesity have been identified, yet the aetiology is not well understood. Traditional statistical methods for analysing observational data are limited by the volume and characteristics of large dataset...
OBJECTIVES: Osteoporosis, prevalent among the elderly population, is primarily diagnosed through bone mineral density (BMD) testing, which has limitations in early detection. This study aims to develop and validate a machine learning approach for ost...
Journal of the American College of Radiology : JACR
Mar 8, 2025
As the use of artificial intelligence (AI) continues to grow in radiology, it has become clear that its real-world performance often differs from that demonstrated in premarket testing, underscoring the need for robust quality management (QM) program...
INTRODUCTION: Imaging studies in the acute care setting, such as the emergency room, have been increasing. In this report, we use the Centers for Medicare and Medicaid services (CMS) database to assess trends in ED chest CT and chest CTA imaging in E...
OBJECTIVE: To develop a machine learning (ML) algorithm capable of identifying children at risk of out-of-home placement among a Medicaid-insured population.
OBJECTIVE: Suicide risk assessment has historically relied heavily on clinical evaluations and patient self-reports. Natural language processing (NLP) of electronic health records (EHRs) provides an alternative approach for extracting risk predictors...
PURPOSE: As generalist large language models (LLMs) become more commonplace, patients will inevitably increasingly turn to these tools instead of traditional search engines. Here, we evaluate publicly available LLM-based chatbots as tools for patient...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.