Artificial Intelligence Medical Compendium

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

Showing 1,531 to 1,540 of 200,346 articles

Explainable machine learning reveals an RBP regulatory logic of exon skipping

bioRxiv May 30, 2026
RNA binding proteins (RBPs) regulate the life cycle of an mRNA, often through RBP-RNA interactions. This life cycle includes splicing, whereby the intronic sequence of a pre-mRNA is removed and the exons are joined together. However, the patterns of ... read more 
systems biology

A pilot assessment of avian communities and soundscapes along an Amazonian fluvial corridor

bioRxiv May 30, 2026
Quantifying biodiversity patterns in remote Amazonian ecosystems remains constrained by the limitations of traditional field surveys. We combined passive acoustic monitoring (PAM), machine learning, and ecoacoustic metrics to assess the taxonomic and... read more 
ecology

Towards A Foundation Model for Clinical Voice Biomarkers

medRxiv May 30, 2026
Vocal biomarkers, encompassing voice and speech, have largely been developed for individual conditions in isolation, limiting their generalizability across diseases and recording settings. To address this, we introduce VoiceFM, a contrastive model th... read more 
health informatics

Deep learning optimisation for cardiology: Neural Architecture Search-driven arrhythmia classification with electrocardiograms

medRxiv May 30, 2026
Cardiovascular disease is the leading cause of death worldwide. Sudden cardiac death (SCD) accounts for roughly 50% of all cardiac deaths. The electrocardiogram (ECG) is widely used for early diagnosis of cardiac disease. However, the complexity of a... read more 
cardiovascular medicine

Boundary-Specific Failure Modes and Safety Trade-offs of Large Language Models in ChronicKidney Disease Renoprotective Therapy Review:A Stratified Synthetic Benchmark

medRxiv May 30, 2026
Background.Renoprotective therapies - SGLT2 inhibitors, finerenone, and renin-angiotensin system inhibitors (RASi) - remain underutilisedin chronic kidney disease (CKD). Large language models (LLMs) may detect therapy omissions, but their performance... read more 
nephrology

High-dimensional Characterization of Genome-Environment Fitness Landscapes in Klebsiella pneumoniae

medRxiv May 30, 2026
Background Bacterial fitness is shaped by interactions between genome variation and environmental context, yet how these interactions determine its predictability and heritability remains unclear. In the clinically important pathogens of Klebsiella p... read more 
genetic and genomic medicine

The Verification Gap: Artificial Intelligence Adoption, Hallucination Awareness, and Verification Practices Among Early Career Medical Researchers in Pakistan

medRxiv May 30, 2026
Artificial intelligence (AI) tools have been rapidly adopted by medical researchers, yet whether early career researchers in low and middle income countries possess the awareness and habits needed to use these tools safely remains poorly documented. ... read more 
health informatics

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 May 30, 2026
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 

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

Advances in nutrition (Bethesda, Md.) May 30, 2026
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 

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.) May 30, 2026
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 
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