Latest AI and machine learning research in clinical trials for healthcare professionals.
OBJECTIVES: Based on ultrasound technology and clinical indicators, this study intends to develop multiple risk prediction models for diabetic peripheral neuropathy (DPN), conduct comparative analyses of these models, and further evaluate and validate the diagnostic efficacy of the optimal model for DPN as well as its potential in clinical application. METHODS: The study included 235 patients grou...
BACKGROUND: Generative artificial intelligence tools such as ChatGPT are increasingly used by medical students for self-directed learning. Although these models demonstrate linguistic fluency, their reliability as supplementary resources for preclinical education remains uncertain. In particular, comparisons with evidence-based references such as UpToDate are lacking. OBJECTIVE: This study evaluat...
OBJECTIVE: To evaluate the efficacy of a clinical decision support system (CDSS) on stroke care quality and clinical outcomes among patients with acut...
The growing threat of antimicrobial resistance, coupled with the challenges of developing new antibiotics, demands innovative therapeutic solutions. A...
BACKGROUND: Artificial intelligence (AI) systems are increasingly deployed in clinical practice, particularly in radiology, pathology, endoscopy, and ...
Machine learning (ML) offers promise for suicide risk stratification in depressed youth, yet its clinical application remains methodologically challen...
BACKGROUND: Reliable quantification of perivascular spaces (PVS) in the basal ganglia (BG) is of growing interest for understanding the glymphatic sys...
Artificial intelligence (AI)-powered diagnostic pathology involves combining traditional histological techniques with computer-assisted AI technology....
BACKGROUND: Artificial intelligence is emerging in healthcare systems. In type 1 diabetes, AI-enabled tools are increasingly used to support nutrition...
PURPOSE: This study compared the effects of written versus visual patient education methods on patient anxiety, procedural comprehension, hemodynamic ...
BACKGROUND: Effective communication is essential in clinical training, yet opportunities for realistic and interactionally authentic practice remain l...
177Lu-PSMA-targeted radioligand therapy (TRT) represents a major advance in managing metastatic castration-resistant prostate cancer (mCRPC), exploiti...
BACKGROUND: Drug-related deaths worldwide are most commonly attributed to opioids. Opioids and other sedative drugs can cause respiratory depression a...
BACKGROUND: Personalized behavioral recommendations through mobile apps have proven effective in preventing serious chronic diseases such as diabetes....
BACKGROUND: Traditional patient education often lacks personalization and engagement, potentially limiting knowledge acquisition and treatment adheren...
BACKGROUND: Hospital Italiano de Buenos Aires (HIBA) has progressively integrated artificial intelligence (AI) technologies into clinical practice ove...
Salmonella is one of the most common foodborne pathogens worldwide, with transmission closely linked to contamination across multiple food products. E...
Early studies of large language models (LLMs) in clinical settings have largely treated artificial intelligence (AI) as a tool rather than an active c...
Accurate measurement of dietary intake remains a cornerstone challenge in optimizing the efficacy of nutritional interventions in human disease. Tradi...
Recent advancements in artificial intelligence (AI) and digital health messaging present opportunities to bridge service health gaps in underserved co...