Artificial Intelligence Medical Compendium

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

Showing 7,281 to 7,290 of 206,272 articles

Circular RNAs in virus-induced cancers: From mechanism to clinical implications.

Biochimica et biophysica acta. Reviews on cancer
Viruses, during their lifecycle, are continuously dependent on host machinery for their survival. Sometimes this dependency leads to uncontrolled cell proliferation in the host, accounting for 12% of virus-associated cancers. Since early times, virus... read more 

Development and External Validation of a Large Language Model-Based Clinical Decision Support System for Colonoscopy Surveillance Intervals.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
BACKGROUND: Adherence to guideline-based colonoscopy surveillance intervals remains suboptimal. Large language models (LLMs) show promise for automating interval assignment, but prior studies relied on proprietary models and have variably assessed ge... read more 

Quality of AI-generated post-operative patient education after minimally invasive gynecologic surgery: A comparative analysis.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: To compare the quality of AI-generated responses to gynecologic post-operative questions with educational materials published by professional societies. DESIGN: Comparative analysis of published and AI-generated patient education rel... read more 

Development of Machine Learning-Driven Dual-Task Gait Test Model for Cognitive Impairment Screening.

Archives of physical medicine and rehabilitation
OBJECTIVE: To develop an artificial intelligence (AI)-aided dual-task gait test model for scalable, high-throughput cognitive impairment screening. DESIGN: A diagnostic case-control study between 2022 and 2023, community-dwelling adults aged ≥60 year... read more 

Frequency-Specific Alterations of Spontaneous Brain Activity in Stroke Patients with Upper Limb Motor Dysfunction: A Multi-Metric rs-fMRI and Machine Learning Study.

Brain research bulletin
BACKGROUND: Post-stroke upper limb motor dysfunction is associated with complex alterations in brain function, but the frequency-specific characteristics of spontaneous local neural activity remain incompletely understood. This study investigated mul... read more 

EEG monitoring in the operating room: current uses and perspectives - a narrative review.

Anaesthesia, critical care & pain medicine
CONTEXT AND IMPORTANCE: With over 300 million surgeries performed under general anaesthesia annually, optimising perioperative brain health has become a critical public health priority. Electroencephalogram (EEG) monitoring, initially conceived to pr... read more 

Does lens opacity matter? The effect of cataract on deep learning based cardiovascular disease risk scores from fundus photos.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To investigate the effect of cataracts on a deep learning (DL) model for cardiovascular disease (CVD) risk prediction. METHODS: This retrospective, dual-cohort study analyzed fundus images at baseline, 1, and 6-months post-cataract surgery f... read more 

Digital and technology-enabled approaches in dietary assessment: addressing bias, error, and feasibility in population- and community-based research.

Advances in nutrition (Bethesda, Md.)
Dietary intake data are essential for understanding diet-disease relationships, informing policy, and evaluating nutrition interventions. This is particularly challenging in population-and community-based research, where varying dietary patterns, mot... read more 

AI-enhanced cardiac digital twins extend drug proarrhythmic risk assessment through experimental data uncertainty propagation and overdose exploration: A loperamide case study.

Regulatory toxicology and pharmacology : RTP
Drug-induced QT interval prolongation is a key biomarker of proarrhythmic risk and central to drug cardiac safety evaluation alongside in vitro assays and animal studies, yet current preclinical frameworks provide limited insight into how experimenta... read more 

TF-DWGNet: a directed weighted graph neural network with tensor fusion for multi-omics cancer subtype classification.

NAR genomics and bioinformatics
Integration and analysis of multi-omics data provide valuable insights for improving cancer subtype classification. However, such data are inherently heterogeneous, high-dimensional, and exhibit complex intra- and inter-modality dependencies. Graph n... read more