Artificial Intelligence Medical Compendium

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

Showing 31,801 to 31,810 of 220,797 articles

SPEAR: Predicting Gene Expression from Single-Cell Chromatin Accessibility

bioRxiv Apr 14, 2026
Single-cell multiome assays enable direct measurement of chromatin accessibility and gene expression within the same cell. Still, most experimental designs remain constrained to two (and, less commonly, three) modalities per cell. This limitation mot... read more 
bioinformatics

A case report on gendered biases in a Finnish healthcare AI assistant

medRxiv Apr 14, 2026
In this study, we investigate gender bias in a Retrieval-Augmented Generation (RAG) based AI assistant developed for Finnish wellbeing services counties. We tested the system using 36 clinically relevant queries, each rendered in three gendered varia... read more 
health informatics

Assessing The Feasibility of AI-Driven Systems for Early Detection of Infectious Diseases at Julius Nyerere International Airport, Tanzania: Policy, Infrastructure, and Ethical Considerations

medRxiv Apr 13, 2026
This study evaluates the feasibility of implementing artificial intelligence (AI)-driven disease surveillance systems at Julius Nyerere International Airport (JNIA) in Tanzania, a key hub for regional and international travel. Through a mixed-methods... read more 
public and global health

Wearable sleep staging using photoplethysmography and accelerometry across sleep apnea severity: a focus on very severe sleep apnea

medRxiv Apr 13, 2026
Study ObjectivesTo evaluate wearable sleep staging across sleep apnea severity, including very severe sleep apnea defined as an apnea-hypopnea index (AHI)[≥] 50 events/h, and to assess how training-set composition affects performance in this subgr... read more 
health informatics

Why Invariant Risk Minimization Fails on TabularData: A Gradient Variance Solution

medRxiv Apr 13, 2026
Machine learning models trained on observational data from one environment frequently fail when deployed in another, because standard learning algorithms exploit spurious correlations alongside causal ones. Invariant learning methods address this pro... read more 
epidemiology

Cross-Cohort Generalizability of Plasma Biomarker Machine Learning Models Reveals Calibration-Driven Degradation in Clinical Utility

medRxiv Apr 13, 2026
BackgroundPlasma biomarkers demonstrate strong within-cohort performance for identifying cerebral amyloid pathology, but their real-world clinical utility depends on generalization across populations and assay platforms. The impact of cross-cohort de... read more 
neurology

LLM-Driven Target Trial Emulation with Human-in-the-Loop Validation for Randomized Trial: Automated Protocol Extraction and Real-World Outcome Evaluation{Psi}

medRxiv Apr 13, 2026
Target trial emulation (TTE) enables causal inference from observational data but remains bottlenecked by manual, expert-dependent protocol operationalization. While large language models (LLMs) have advanced clinical knowledge extraction and code ge... read more 
health informatics

No One Left Behind: Adaptive Tablet Modalities for Digitally Excluded Emergency Department Patients Design, Implementation, and Social Evidence for an Impairment-First Interface

medRxiv Apr 13, 2026
Background: The urgent care departments in Europe face a structural paradox: accelerating digitalisation is accompanied by a patient population that is disproportionately unable to engage with standard digital tools. An internal analysis at the Emerg... read more 
health systems and quality improvement

Greater lean-body-mass decline with tirzepatide than semaglutide in routine care, revealed by body-composition digital phenotyping

medRxiv Apr 13, 2026
GLP-1 receptor agonists induce substantial weight loss, but the extent to which lean tissue and physical function are preserved in routine care remains poorly understood. Using an EHR-linked body-composition digital phenotyping pipeline with LLM-base... read more 
endocrinology

Virtual Spectral Decomposition with Dendritic Tile Selection: An Explainable AI Framework for Multimodal Tissue Composition Analysis and Immune Phenotyping Across Pancreatic, Lung, and Breast Cancer

medRxiv Apr 13, 2026
Background: Current deep learning models in computational pathology, radiology, and digital pathology produce opaque predictions that lack the explainable artificial intelligence (xAI) capabilities required for clinical adoption. Despite achieving ra... read more 
oncology
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