Latest AI and machine learning research in risk management for healthcare professionals.
BACKGROUND: Knowledge Translation (KT) research investigates methods to promote the uptake of research by practitioners, managers and policy-makers. Rooted in decades of interdisciplinary scholarship showing that evidence use is shaped by social sense‑making, institutions and politics, KT has moved beyond a linear "research to policy" model. Yet, persistent gaps between evidence and decision‑makin...
BACKGROUND: Artificial intelligence is increasingly embedded in clinical practice and medical education, yet the psychological determinants of students' readiness remain poorly understood. We are aware of no study that has simultaneously examined personality traits, technology affinity and AI readiness in a single cohort. METHODS: In a cross-sectional online survey using convenience and snowball s...
BACKGROUND: Operating room (OR)-to-intensive care unit (ICU) handoffs are among the most complex and high-risk communication events in perioperative c...
Music engages sensory, motor, cognitive, and emotional systems, making it a powerful model for studying experience-dependent neuroplasticity. Although...
BACKGROUND: Bronchopulmonary dysplasia (BPD) remains a major complication of extreme prematurity, but diagnosis and severity classification have becom...
OBJECTIVE: The American Board of Surgery In-Training Examination (ABSITE) assesses surgical resident knowledge, but manual analysis of program-wide da...
INTRODUCTION: Artificial intelligence (AI) is increasingly used in tuberculosis (TB) diagnosis, but its clinical adoption depends not only on accuracy...
BACKGROUND: This joint American Society of Neuroradiology-European Society of Neuroradiology (ASNR-ESNR) white paper addresses the call for sustainabl...
Artificial intelligence (AI) tools are rapidly being adopted in veterinary medicine. Unlike human medicine, where the Food and Drug Administration has...
Modern steganalysis achieves strong performance on controlled benchmarks, yet existing datasets fail to capture the diversity of real-world JPEG image...
OBJECTIVES: To evaluate the diagnostic accuracy and quantitative agreement of A-LIKNet (attention-incorporated network for sharing low-rank, image, an...
OBJECTIVES: Effective dose management in computed tomography is impeded by 2 key operational challenges: error-prone manual protocol mapping and the h...
BACKGROUND: Determination of death by neurologic criteria (DNC) relies on clinical examination, provided no confounding conditions affect reliability....
Recent regulation, the EU AI Act and ISO/IECÂ 42001, requires organizations deploying high-risk artificial intelligence (AI) systems to identify, asses...
BACKGROUND: Quantification of rice root anatomical traits such as cortical aerenchyma lacunae is key to understanding rice adaptation to diverse water...
OBJECTIVE: This systematic review aimed to systematically evaluate the methodological quality and predictive performance of existing prognostic models...
INTRODUCTION: The rapid integration of artificial intelligence (AI) technologies in healthcare, ranging from diagnostic tools to clinical decision sup...
BACKGROUND: The check-in before imaging is an often underestimated but clinically critical step in the radiological patient journey. In computed tomog...
BACKGROUND: Cerebral palsy (CP) is a prevalent neurodevelopmental disorder in children, often leading to long-term motor impairments. Rehabilitation r...
BACKGROUND: Preexposure prophylaxis (PrEP) is a key biomedical HIV prevention strategy that relies heavily on adherence for optimal effectiveness. In ...