Artificial Intelligence Medical Compendium

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

Showing 54,701 to 54,710 of 226,183 articles

Machine learning-based prediction of CAC-defined cardiovascular risk using routine health examination data: a retrospective cross-sectional study in a Taiwanese population.

Journal of the Formosan Medical Association = Taiwan yi zhi Feb 3, 2026
BACKGROUND: Early identification of individuals at elevated cardiovascular risk using routine health examination data is essential for preventive cardiology. Machine learning (ML) offers a scalable and non-invasive approach to enhance risk stratifica... read more 

Air quality prediction model based on deep learning hybrid framework.

Scientific reports Feb 3, 2026
As modernization and industrialization continue to accelerate, air pollution has become an increasingly pressing problem. Air quality prediction is considered an essential technical support for air pollution prevention and control. To achieve more ac... read more 

AI Agent for Delirium Screening among Patients in Oncology and Cardiac Intensive Care Units: A Proof-of-Concept Study.

European journal of cardiovascular nursing Feb 3, 2026
AIM: To develop and evaluate an autonomous artificial intelligence (AI) agent to support nurse-led delirium screening and guideline-concordant prevention and management. METHODS AND RESULTS: We constructed a delirium-specific knowledge graph from pub... read more 

Machine learning-based COVID-19 prognostic models lag behind in reporting quality: findings from a TRIPOD/TRIPOD + AI systematic review.

Diagnostic and prognostic research Feb 3, 2026
BACKGROUND: Reporting of COVID-19 prognostic models frequently falls short of established standards. The TRIPOD checklist and its 2024 AI extension (TRIPOD + AI) provide a comprehensive framework for assessing reporting quality. We therefore evaluate... read more 

Implementation of AI systems in the clinical laboratory: insights from an expert survey and recommendations for best practice.

Clinical chemistry and laboratory medicine Feb 3, 2026
OBJECTIVES: Despite growing interest in artificial intelligence (AI) and machine learning (ML), many laboratory professionals lack experience with developing in-house AI systems or implementing those supplied by external providers. The IFCC Committee... read more 

Prediction of risk factors and electrocardiographic changes in chronic kidney disease patients.

Journal of basic and clinical physiology and pharmacology Feb 3, 2026
OBJECTIVES: Chronic kidney disease (CKD) is a global health issue with significant morbidity and mortality, particularly due to cardiovascular events. Early identification and management of risk factors are crucial to prevent CKD progression and comp... read more 

K-MIMIC: a nationwide Korean multi-institutional Multimodal intensive care dataset.

Korean journal of anesthesiology Feb 3, 2026
BACKGROUND: Recent advancements in critical care have highlighted the need for comprehensive, multimodal datasets to support clinical decision-making and advancing artificial intelligence (AI) research. However, such datasets are scarce in Asia. We d... read more 

Comparison of large language models and conventional machine learning in postoperative outcome prediction: a retrospective, multi-national development and validation study.

Korean journal of anesthesiology Feb 3, 2026
BACKGROUND: Conventional machine learning (ML) models for predicting surgical outcomes have limitations in generalizability We explored large language models (LLMs) as scalable alternatives to conventional ML models in predicting postoperative outcom... read more 

Characteristics of electroencephalographic changes induced by different hypnotics in elderly patients: a narrative review.

Korean journal of anesthesiology Feb 3, 2026
Aging is associated with widespread structural and functional changes in the brain including reduced neural plasticity, slower information processing, and impaired network integration. These age-related alterations influence the brain's response to a... read more 

Mechanistic principles of antimicrobial peptides uncovered by charge density-based machine learning.

Chemical communications (Cambridge, England) Feb 3, 2026
Antimicrobial peptides (AMPs) are emerging as potent alternatives to conventional antibiotics, yet their diverse nature due to divergent mechanisms of action hinders rational design. Here, we present an electrostatics-stratified computational framewo... read more 
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