Artificial Intelligence Medical Compendium

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

Showing 36,761 to 36,770 of 223,469 articles

Nanoscale Podocyte Morphometrics Predict Disease Progression in IgA Nephropathy

medRxiv Apr 1, 2026
Introduction: Podocyte injury is central to the pathogenesis of most glomerulonephritides (GN) and causes segmental glomerulosclerotic lesions that predict progression in IgA Nephropathy (IgAN). Recent advances in high-resolution microscopy and AI-as... read more 
nephrology

Governance, Accountability and Post-Deployment Monitoring Preferences for AI Integration in West African Clinical Practice: A Mixed-Methods Study

medRxiv Apr 1, 2026
Background: The integration of artificial intelligence (AI) into clinical practice holds transformative potential for healthcare in West Africa, but safe deployment requires context-appropriate governance, accountability, and post-deployment monitori... read more 
health informatics

Predicting highly pathogenic avian influenza H5N1 outbreak risk using extreme weather and bird migration data in machine learning models

medRxiv Apr 1, 2026
Background. Climate change is intensifying extreme weather events (EWEs) with potentially profound consequences for zoonotic disease dynamics, yet the mechanisms linking EWEs to highly pathogenic avian influenza (HPAI) H5N1 outbreaks remain poorly ch... read more 
epidemiology

A Deployable Explainable Deep Learning System for Tuberculosis Detection from Chest X-Rays in Resource-Constrained High-Burden Settings

medRxiv Apr 1, 2026
Abstract Objectives: To develop and evaluate a deployable deep learning system with Gradient-weighted Class Activation Mapping (Grad-CAM) for tuberculosis screening from chest radiographs and to assess its classification performance and explainabilit... read more 
radiology and imaging

Evaluating the Large Language Model-Based Quality Assurance Tool for Auto-Contouring

medRxiv Apr 1, 2026
Purpose: Manual verification of AI-based auto-contouring is labor-intensive and prone to fatigue-related errors. This study developed the large language model (LLM)-based automated Quality Assurance (QA) for auto-contouring (LAQUA) system using a mul... read more 
radiology and imaging

DR. INFO at the Point of Care: A Prospective Pilot Study of an Agentic AI Clinical Assistant

medRxiv Apr 1, 2026
Background: Clinical documentation and information retrieval consume over half of physicians working hours, contributing to cognitive overload and burnout. While artificial intelligence offers a potential solution, concerns over hallucinations and so... read more 
health informatics

MedScope: A Lightweight Benchmark of Open-Source Large Language Models for Medical Question Answering

medRxiv Apr 1, 2026
The rapid development of large language models (LLMs) has stimulated growing interest in their use for medical question answering and clinical decision support. However, compared with frontier proprietary systems, the empirical understanding of light... read more 
health informatics

Development and Pilot Validation of ABHA-O-SHINE: An AI-Ready Oral Health Risk and Insurance Prediction Framework within the Ayushman Bharat Digital Ecosystem

medRxiv Apr 1, 2026
Background: Oral health remains inadequately integrated within the Ayushman Bharat Digital Mission (ABDM), particularly in terms of structured risk assessment and its linkage to insurance-based decision-making. There is a growing need for scalable mo... read more 
public and global health

Combining Token Classification With Large Language Model Revision for Age-Friendly 4M Entity Recognition From Nursing Home Text Messages: Development and Evaluation Study

medRxiv Apr 1, 2026
Background: Secure text messages (TMs) exchanged among interdisciplinary care teams in nursing homes (NHs) contain clinical information that aligns with the Age-Friendly Health Systems 4Ms: What Matters, Medication, Mentation, and Mobility, yet, this... read more 
health informatics

Improving Glioblastoma Classification Using Quantitative Transport Mapping with a Synthetic Data Trained Deep Neural Network

medRxiv Apr 1, 2026
Purpose: To develop a deep neural network-based, AIF-free, perfusion estimation method (QTMnet) for improved performance on glioma classification. Methods: A globally defined arterial input function (AIF) is needed to recover perfusion parameters in ... read more 
radiology and imaging
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