Latest AI and machine learning research in clinical trials for healthcare professionals.
BACKGROUND: Artificial intelligence (AI) systems are increasingly deployed in clinical practice, particularly in radiology, pathology, endoscopy, and decision support. While these tools improve efficiency and accuracy, concerns have arisen about deskilling-the erosion of physicians' expertise due to reliance on automation. MATERIALS AND METHODS: We conducted a narrative review of empirical studies...
Machine learning (ML) offers promise for suicide risk stratification in depressed youth, yet its clinical application remains methodologically challenging. Using prospective data from 602 Chinese patients aged 15-24 years collected between January 2022 and June 2023, we developed ML models to predict suicide attempts within 30 days after treatment. From 102 clinical and psychosocial predictors, on...
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...
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...
Recent advancements in artificial intelligence (AI) and digital health messaging present opportunities to bridge service health gaps in underserved co...
BACKGROUND: Emergency medical dispatch is a critical, high-stakes process where dispatcher decisions directly impact patient outcomes. While standardi...
Background: The impact of artificial intelligence (AI) tools for lung nodule evaluation on low-dose CT (LDCT) have been evaluated primarily using expe...
BACKGROUND AND OBJECTIVES: Family caregivers face elevated risks for mental and physical health issues but have difficulty accessing informational and...
OBJECTIVES: To assess patient awareness, trust, perceived benefits, and risks of artificial intelligence (AI) in clinical care within an urban safety-...
The integration of artificial intelligence (AI) into healthcare is accelerating and maternity care is at a pivotal moment for the strategic implementa...
Smart polymers have played great role in enhancing nanomedical application areas in drug delivery, diagnosis and environment sensitive treatment syste...