Artificial Intelligence Medical Compendium

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

Showing 4,951 to 4,960 of 204,028 articles

Decoding Cognitive States from fMRI Using Classical Machine Learning and Temporal Dynamics Analysis: An Interpretable Approach Using the Human Connectome Project

bioRxiv Jun 1, 2026
We propose a rigorous and reproducible methodology for analyzing functional MRI data, aimed at: (1) demonstrate their efficiency in classifying task-induced brain states with a limited amount of data, (2) present a methodology to identify brain regio... read more 
neuroscience

Forecasting novel therapeutic development in biomedical research

bioRxiv Jun 1, 2026
Early identification of promising drug research topics is challenging yet crucial for the scientific community to accelerate the development of novel therapeutics. In this work, we leverage large-scale public data from the biomedical literature to ex... read more 
scientific communication and education

Case-level artificial intelligence for multi-photo teledermatology submissions: development and internal validation using patient-submitted dermatology images

medRxiv Jun 1, 2026
Background: Store-and-forward teledermatology commonly relies on several patient-submitted photographs of the same concern, but most dermatology artificial intelligence models classify single images independently. Objective: To develop and internally... read more 
dermatology

Real-world impact of a sepsis early detection model integrated into clinical workflow: a quasi-experimental study

medRxiv Jun 1, 2026
Background: Sepsis is a life-threatening condition in which delayed recognition and treatment are associated with increased mortality. While predictive models such as Epic's Early Detection of Sepsis Model (ESM) were developed to support early interv... read more 
health informatics

Relationship Extraction for Adverse Drug Events in Clinical Notes Using Large Language Models

medRxiv Jun 1, 2026
Background: Adverse drug events (ADEs) are a critical indicator of patient safety but are often documented only in free-text clinical notes. The potential of recent advances in natural language processing (NLP), particularly generative large language... read more 
health informatics

Algorithmic Versus Expert Rankings of Large Language Models in Peritoneal Dialysis Prescription Review: A Trap-Embedded Synthetic Benchmark

medRxiv Jun 1, 2026
Background: Clinical LLM benchmarks rarely test whether algorithmic rankings agree with expert clinical judgment. We developed a trap-embedded peritoneal dialysis (PD) benchmark comparing multiple scoring constructs with blinded nephrologist ratings.... read more 
nephrology

Developing and Evaluating Deep Learning Approaches for Visual Field Denoising in Glaucoma

medRxiv Jun 1, 2026
Purpose To investigate the relative efficacy of nine distinct visual field (VF) denoising artificial intelligence (AI) methods and a pathology-aware AI strategy to discourage over-correction of glaucomatous defects. Design Retrospective study. Partic... read more 
ophthalmology

Stigmatizing Language Detection in Opioid Use Disorder Patient-Directed Discharge Clinical Documentation: A Privacy-Preserving Analysis Using a Locally Deployed Large Language Model

medRxiv Jun 1, 2026
Objective: Stigmatizing language in the electronic health record (EHR) has been associated with adverse patient experience in substance use disorder care, including opioid use disorder (OUD). This study evaluated a privacy-preserving, locally-deploye... read more 
health informatics

Sensitive Glioma Detection and Recurrence Monitoring Using a Machine Learning Model Based on Circulating Monocytes

medRxiv Jun 1, 2026
Background: Non-invasive diagnosis, reliable recurrence surveillance remain critical unmet needs in gliomas. Glioma induces profound systemic immune alterations despite its anatomical confinement to the central nervous system. Circulating immune cell... read more 
oncology

Multi-Agent AI for Chest Radiography: A Sequential Segmentation and LLM-Driven Consultative Tool for Medical Training

medRxiv Jun 1, 2026
Background: Traditional diagnostic models lack explainability, while multimodal language models prone to hallucination remain unsafe for medical education. An interactive, risk-free artificial intelligence framework is required to serve as a reliable... read more 
health informatics
Popular Topics
Recent Journals