Artificial Intelligence Medical Compendium

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

Showing 5,711 to 5,720 of 205,404 articles

Audited large language model triage for systematic review screening in national clinical guideline production: validation and prospective deployment

medRxiv Jun 3, 2026
Title and abstract screening limit the timeliness of systematic reviews used for clinical guidelines. We evaluated audited large language model (LLM) triage at Sweden's National Board of Health and Welfare. Ten LLMs from five model families were test... read more 
health informatics

Interpretable machine learning for coeliac disease diagnosis: quantitative morphometry of duodenal biopsies

medRxiv Jun 3, 2026
Background Coeliac disease affects approximately 1% of the global population and remains substantially underdiagnosed. Histopathological assessment of duodenal biopsies is the diagnostic gold standard but is subject to approximately 20% inter-observe... read more 
pathology

Leveraging Digitization, Archiving and Artificial Intelligence to Re-examine Predictors of Sustained Mental Health Care Engagement in Ugandan First-Episode Psychosis Patients: A Study Protocol

medRxiv Jun 3, 2026
Background: We previously examined the burden and predictors of sustained mental health care engagement in Ugandan first episode psychosis patients by retrospective chart review methods. However, the extensive requirements of chart reviews meant that... read more 
psychiatry and clinical psychology

Simple cumulative weighting of routine surveillance data identifies epidemic wave origins more accurately than a large language model: evidence from eight COVID-19 waves in Japan

medRxiv Jun 3, 2026
Identifying the origin of an emerging epidemic wave within days of onset could enable targeted response before national spread, yet current methods rely on genomic sequencing that lags clinical detection by 2-4 weeks. We analysed daily COVID-19 cases... read more 
public and global health

Automated assessment of neonatal internal capsule maturation on T2-weighted MRI across 7T and 3T

medRxiv Jun 3, 2026
Motivation: Quantitative assessment of neonatal internal capsule (IC) maturation remains largely reliant on qual- itative visual evaluation, limiting objectivity and scalability. Approach: We developed a fully automated 3D deep learning framework for... read more 
radiology and imaging

MyoPath: A Deep Learning Pipeline for Objective Morphometric Assessment of Skeletal Muscle Biopsies

medRxiv Jun 3, 2026
Histopathological evaluation of skeletal muscle biopsies relies on subjective, semi-quantitative assessment with no standardized grading system. We developed a four-tissue deep learning segmentation pipeline using Cellpose-SAM for myofiber instance s... read more 
radiology and imaging

Automatic Speech Recognition and Phonetics-Informed Sentence Design for Spastic Dysarthria Detection and Corticobulbar Lesion Localization

medRxiv Jun 3, 2026
Spastic dysarthria diagnosis through subjective neurologist auditory-perceptual assessment remains standard practice despite known inaccuracy. To address this gap, we developed an objective framework grounded in phonetic evidence that spastic dysarth... read more 
neurology

Semi-automated detection of cleaning interactions using supervised machine learning.

Scientific reports Jun 3, 2026
Cleaner fish engage in mutualistic interactions by removing ectoparasites from client species, a behaviour that has traditionally been quantified through labour-intensive manual video analysis. This method is not only time-consuming but also suscepti... read more 

Machine learning and deep learning-based drug-drug interactions prediction: a systematic review focused on anticancer drugs.

NPJ precision oncology Jun 3, 2026
Cancer patients are particularly susceptible to Drug-Drug Interactions (DDIs) due to frequent polypharmacy in oncology care. Co-administered drugs can increase toxicity or reduce effectiveness, potentially causing serious adverse events-for example, ... read more 

Tri-MCA fusion: cross-modal attention and dynamic gating for multimodal sentiment analysis.

Scientific reports Jun 3, 2026
Multimodal sentiment analysis aims to automatically infer human emotions by jointly analyzing information from multiple modalities, such as text, audio, and visual signals. Although recent deep learning approaches have significantly improved multimod... read more 
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