Latest AI and machine learning research in clinical trials for healthcare professionals.
BACKGROUND: Large language models (LLMs) are rapidly emerging in health care, offering opportunities in decision support, education, and research, but raising critical concerns about safety, reliability, and ethics. Although several guidelines for trustworthy AI exist in business and technology, few systematic reviews have applied them to medical contexts. OBJECTIVE: This study aimed to conduct a ...
BACKGROUND: Electrographic flow (EGF) mapping is an FDA 510(k)-cleared method for visualizing atrial activation wavefronts in atrial fibrillation (AF). Its clinical efficacy in detecting AF sources was demonstrated in the FLOW-AF randomized controlled trial, and the underlying machine learning strategy used to develop and refine EGF source detection has been recently detailed. However, EGF mapping...
INTRODUCTION: Large language models (LLMs) are increasingly utilized for medical and dental information retrieval, yet their ability to interpret auth...
Artificial intelligence (AI) has entered psychiatry at scale, yet its clinical impact remains constrained by a sizable gap between technical validatio...
Over 40% of Obsessive-Compulsive Disorder (OCD) patients do not respond to common treatments. This study was a secondary analysis of data from a rando...
Robot-assisted vascular intervention may reduce occupational radiation exposure, improve procedural stability, and expand access to specialized endova...
BACKGROUND: This study aimed to evaluate the influence of a pre-commercial artificial intelligence (AI)-based software system on endosonographers' per...
BACKGROUND: Integration of large language models (LLMs) into health care has accelerated rapidly, yet reliability concerns pose potential risks to pat...
Prospective evidence for artificial intelligence (AI)-based clinical decision support in emergency departments remains limited. Here we conducted a DE...
Liver malignancies are frequently evaluated on contrast-enhanced computed tomography (CE-CT), but missed or delayed diagnoses remain a clinically impo...
BACKGROUND: Digital health communication is gaining importance as health care systems face increasing demand and structural constraints. Generative ar...
Aging is a significant risk factor of neurodegenerative disorders (NDs) such as Huntington's, Alzheimer's, Parkinson's, amyotrophic lateral sclerosis ...
Thermal ablation (TA), including microwave ablation, radiofrequency ablation, and cryoablation, is increasingly used as a surgical alternative for T1a...
BackgroundThe rise of digital platforms and algorithmically-managed labour is reshaping traditional understandings of job quality, safety, and wellbei...
BACKGROUND: Secondary prevention of coronary heart disease (CHD) remains suboptimal due to fragmented care and therapeutic inertia. While digital heal...
BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children and adolescents. Digital therapeuti...
This study examines predictors of students' perceived learning effectiveness from generative artificial intelligence (GenAI) in higher education by in...
PURPOSE: To evaluate ChatGPT-4o in a real-world urological multidisciplinary tumour board (MTB), with concordance for the final clinical recommendatio...
BACKGROUND: AI has shown significant potential in intensive care unit (ICU) nursing practice, enhancing efficiency, decision-making, and patient safet...
BACKGROUND: Thailand is undergoing a rapid demographic transition, with an estimated 28% of the population expected to be aged 60 years or older by 20...