Artificial Intelligence Medical Compendium

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

Showing 22,091 to 22,100 of 216,627 articles

Claim-Level Transparency Analysis of LLM-Generated Diagnostic Reports: A Metabolic and Endocrine Biomarker Study

bioRxiv May 6, 2026
Large language models are increasingly deployed in clinical decision-support contexts, yet systematic evaluation of their factual reliability in generating patient-specific diagnostic reports remains sparse, particularly for laboratory interpretation... read more 
systems biology

Integrated Multi-Omics Analysis for the Identification of Disease-Associated Variations and Prognostic Biomarkers in Triple-Negative Breast Cancer (TNBC)

bioRxiv May 6, 2026
Background: Triple-negative breast cancer (TNBC) exhibits substantial molecular heterogeneity and lacks targeted receptor therapies. Single-omic approaches inadequately capture its regulatory complexity, necessitating integrated multi-omic frameworks... read more 
bioinformatics

Evaluating Reference-Independent Pipelines for the Detection of Spreading Organisms in Metagenomic Datasets

bioRxiv May 6, 2026
The emergence of unidentified pathogens, or "Disease X," poses a significant threat to global health, necessitating the development of proactive surveillance strategies for the wildlife and human virosphere. Since novel viruses often lack universal g... read more 
bioinformatics

Novel linkage disequilibrium-based genotype-by-environmental interaction method for genomic prediction of cotton yield and fibre quality traits

bioRxiv May 6, 2026
Genomic prediction (GP) across diverse environments has a potential to accelerate genetic gain in cotton breeding programs. A major challenge in GP is modelling genotype-by-environment interactions (GEI), which is essential for selecting stable and h... read more 
plant biology

PEPR-GNN: Perturbation-Enhancer-Promoter-RNA Graph Neural Networks for Multiome Perturb-Seq modeling of regulomes

bioRxiv May 6, 2026
Cellular reprogramming is a complex interplay between perturbations and regulatory elements, culminating in gene expression changes. Current computational approaches do not explicitly model these regulatory interactions. Here, we first performed comb... read more 
genomics

Patterns and Predictors of Artificial Intelligence Use Among Healthcare Professionals in the United States and United Kingdom: A Cross-National Survey

medRxiv May 6, 2026
Objective: We surveyed 524 healthcare professionals (HCPs) in the United States and United Kingdom to examine workplace generative AI use, access, and barriers in two high-maturity health settings. Methods: This cross-sectional survey compared AI usa... read more 
health informatics

Heterogeneous Treatment Effect for Targeted Temperature Management After Cardiac Arrest: A Causal Machine Learning Analysis

medRxiv May 6, 2026
ABSTRACT Objectives: To determine whether heterogeneous treatment effects (HTE) explain the inconclusive results of targeted temperature management (TTM) trials after cardiac arrest, using causal machine learning across four datasets. Design: Seconda... read more 
intensive care and critical care medicine

Multi-LLM Disagreement as a Scalable Detector of Human Annotation Errors in Structured Data from Clinical Free-Text

medRxiv May 6, 2026
Abstract Objective: Structured extraction from clinical free-text depends on human annotators whose labels are susceptible to errors and knowledge-driven mistakes; exhaustive quality control is impractical at scale. We evaluate whether disagreement a... read more 
health systems and quality improvement

Early Detection of Rare Disease Using Hierarchical Set-to-Sequence Modeling of Structured Electronic Health Records

medRxiv May 6, 2026
Rare diseases are characterized by heterogeneous, weak, and sparse phenotypic signals that emerge gradually across longitudinal clinical visits, making early detection a persistent challenge. In this study, we propose a hierarchical set-to-sequence (... read more 
health informatics

PD Union An Automated Pharmacodynamic Modeling Framework Based on a Unified Mechanistic Skeleton and Machine Learning Assistance

medRxiv May 6, 2026
Abstract Objective: Conventional pharmacodynamic (PD) modeling workflows require manual model selection, repeated equation rewriting, and empirical parameter adjustment, resulting in limited automation, high cross-scenario migration costs, and insuff... read more 
pharmacology and therapeutics
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