Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 1,231 to 1,240 of 213,401 articles

The Science of Preventing Delirium: Trends, Knowledge Gaps, and Future Directions Revealed Through Bibliometric Insights.

Journal of perianesthesia nursing : official journal of the American Society of PeriAnesthesia Nurses Jul 17, 2026
PURPOSE: To examine global research trends in delirium prevention through a bibliometric analysis and provide a structured overview of its development and emerging directions. DESIGN: A bibliometric analysis. METHODS: Data were retrieved from the Web... read more 

Integrated statistical and machine-learning optimization for enhanced heparosan production by Lactococcus lactis.

Preparative biochemistry & biotechnology Jul 17, 2026
Lactococcus lactis SH6 was engineered for heterologous heparosan production, and its growth medium was optimized using a combination of experimental design and machine learning (ML). One-factor-at-a-time shake flask experiments revealed glucose (10 g... read more 

Recent developments in the therapeutic management of acid-related gastrointestinal diseases.

Expert review of gastroenterology & hepatology Jul 17, 2026
INTRODUCTION: Acid-related gastrointestinal diseases, particularly gastroesophageal reflux disease (GERD) and peptic ulcer disease (PUD), remain major global health burdens despite decades of proton pump inhibitor (PPI)-based therapy. Persistent symp... read more 

Exploring the role of generative artificial intelligence in enhancing clinical skills training: A bibliometric analysis.

Medicine Jul 17, 2026
BACKGROUND: Traditional clinical skills training faces challenges such as limited standardized patient resources, high costs of simulation equipment, and restricted opportunities for repeated practice. Generative artificial intelligence (GAI), partic... read more 

Predicting severe COVID-19 in elderly patients using routine laboratory indicators: Diagnostic accuracy of machine learning models.

Medicine Jul 17, 2026
To enable early warning of severe 2019 coronavirus disease in elderly patients, this study collected routine laboratory indicators and clinical parameters to construct and validate clinical models to predict the risk of severe disease. A total of 123... read more 

Knowledge graph visualization and bibliometric analysis of research on coronary artery lesions in Kawasaki disease.

Medicine Jul 17, 2026
BACKGROUND: Coronary artery lesions (CAL) complicating Kawasaki disease (KD) are a central concern affecting the long-term cardiovascular health of affected children. This study aimed to systematically depict the macro landscape, knowledge structure,... read more 

Evaluating the quality, understandability, actionability, and readability of ChatGPT-generated patient information on overactive bladder: A cross-sectional study.

Medicine Jul 17, 2026
This cross-sectional study aimed to evaluate the quality, understandability, actionability, and readability of patient-oriented information generated by ChatGPT regarding overactive bladder (OAB). A total of 32 frequently asked patient questions rela... read more 

Attitudes, usage patterns, and learning interests of medical students toward DeepSeek in medical education: A cross-sectional survey.

Medicine Jul 17, 2026
The integration of artificial intelligence (AI) tools like DeepSeek into scientific research offers new opportunities for efficiency and innovation. However, attitudes and adoption among medical students remain underexplored. This study aims to inves... read more 

Construction and validation of a machine learning-based risk prediction model for venous thromboembolism in older adult patients: A multifactorial analysis of 28,231 cases.

Medicine Jul 17, 2026
Venous thromboembolism (VTE) is a leading preventable cause of in-hospital mortality in older adults, yet early risk stratification remains a key clinical challenge. This study aimed to develop and internally validate an explainable machine learning ... read more 

Machine learning models of depressive symptoms in middle-aged and elderly patients with chronic kidney disease: A cross-sectional study based on CHARLS.

Medicine Jul 17, 2026
This study aimed to develop and compare the performance of machine learning models in identifying depressive symptom status among middle-aged and elderly patients with chronic kidney disease (CKD), while identifying key factors that influence depress... read more 
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