Latest AI and machine learning research in clinical trials for healthcare professionals.
This study examines how technological affordances shape applicants' continued intention to use AI-enabled recruitment systems, with particular attention to differences between neurodivergent and neurotypical applicants. Grounded in the Elaboration Likelihood Model, the study investigates association, editability, persistence, and anonymity as evaluative cues and examines the role of trust in appli...
Saphenous vein graft (SVG) percutaneous coronary intervention (PCI) remains technically challenging and clinically high risk due to the friable, thrombus-rich nature of SVG lesions, which predispose to distal embolization, no-reflow, and periprocedural myocardial infarction (MI). The role of embolic protection devices in contemporary practice remains unclear. Although early randomized trials demon...
OBJECTIVE: To synthesize contemporary developments in head and neck oncologic free flap reconstruction, with emphasis on perioperative physiologic opt...
Drug repurposing involves the discovery of new therapeutic uses of existing drugs that have already been approved by the regulatory authorities. It pr...
OBJECTIVE: Artificial intelligence (AI) demonstrates significant potential in medical imaging diagnosis, yet its real-world clinical value requires va...
Transfusion medicine has practiced a form of precision medicine for decades through compatibility testing, infectious disease screening, component man...
BACKGROUND: Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are 2 of the leading causes of vision loss worldwide. As population a...
BACKGROUND: Generative artificial intelligence (GenAI) can automate time-intensive tasks and support clinical decision-making in care settings. Nurses...
Generative artificial intelligence offers personalized patient education, yet clinical inaccuracy and lack of theoretical grounding threaten health ca...
BACKGROUND: Diabetic foot ulcers remain a leading cause of non-traumatic amputations worldwide, necessitating precise patient education and clinical m...
Growing evidence indicates that disruption of the microbiota-gut-brain (MGB) axis is a key factor in autism spectrum disorder (ASD), affecting neurode...
INTRODUCTION: Drug discovery remains constrained by high attrition rates and the fragmented evaluation of exposure, efficacy, and safety. Mechanistic ...
Chronic pain (CP) disproportionately affects underserved populations who often experience barriers to evidence-based nonpharmacologic treatments. Digi...
BACKGROUND: Large language models (LLMs) are increasingly embedded in medical education and clinical care settings, yet contemporary Canadian data des...
BACKGROUND: Nurse burnout is a pervasive global problem. Cognitive behavioral therapy (CBT) has been shown to reduce burnout; however, most digital CB...
BACKGROUND: The diagnosis and monitoring of Alzheimer disease (AD) currently rely on clinician-administered, in-person, and cross-sectional pen-and-pa...
BACKGROUND: Clinical triage requires integrating multiple information sources to identify patients at risk of deterioration. Tools capturing global he...
A fully automated 2-dimensional imaging system that uses machine learning to produce real-time mobility scores has been developed and previously exter...
The growing integration of artificial intelligence tools, particularly conversational agents, is transforming how consumers access information, includ...
BACKGROUND: Hospital discharge reports (HDRs) support continuity of care; yet, their specialized terminology may hinder patient understanding and post...