Artificial Intelligence Medical Compendium

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

Showing 6,241 to 6,250 of 205,745 articles

Quantitative evaluation of an artificial intelligence-driven remote monitoring system for occlusion assessment using patient-captured images.

The Angle orthodontist Jun 2, 2026
OBJECTIVES: To evaluate the accuracy of an artificial intelligence (AI) model developed by DentalMonitoring for assessing occlusal parameters from patient-acquired intraoral images, using intraoral scanner (IOS)-derived three-dimensional (3D)measurem... read more 

Liquid-liquid phase separation in metabolic engineering: Mechanistic insights, emerging applications, and future challenges.

Biotechnology advances Jun 2, 2026
Mechanistic studies of liquid-liquid phase separation (LLPS) have increasingly revealed that cells achieve multiscale and highly precise regulation of metabolic activities and biochemical reaction networks through the formation of membraneless organe... read more 

Assessing Military Artificial Intelligence Responses to Anterior Cruciate Ligament Injury Frequently Asked Questions.

Military medicine Jun 2, 2026
INTRODUCTION: Artificial intelligence is gaining significant traction, particularly in the orthopedic literature. To date, there has been no published literature on the use of specific military AI tools such as NIPR-GPT. The accuracy, reliability, an... read more 

A Deep Learning-Based Predictive Algorithm for Metabolic Syndrome Detection in the U.S. Population

medRxiv Jun 2, 2026
Objective To develop clinically operational, population-representative risk-score models for detecting metabolic syndrome (MetS) in U.S. adults by incorporating the NHANES survey design. Research Design and Methods We analyzed 36,812 U.S. adults from... read more 
endocrinology

Explainable AI and public reactions to AI-involved adverse diagnostic events: a vignette study

medRxiv Jun 2, 2026
Artificial intelligence (AI) is increasingly incorporated into diagnostic decision-making, raising questions about physician responsibility following AI-involved adverse diagnostic events. Explainable AI (XAI) has been proposed to improve transparenc... read more 
health informatics

Combined values alignment and epistemic verification prevent delusional reinforcement in conversational AI agents

medRxiv Jun 2, 2026
Conversational AI is being deployed into medical decision support, mental-health triage, and social companionship, where reinforcement of a user's false or delusional belief can cause direct harm. Most deployed safety techniques are evaluated for fac... read more 
health informatics

Conformal Prediction and Ensemble Learning for Uncertainty-Aware ICU Mortality Stratification

medRxiv Jun 2, 2026
Background. Conventional ICU severity scores - SOFA, qSOFA, and APACHE-II - use additive integer weightings that cannot capture non-linear organ failure interactions; prospective validations consistently report AUC near 0.73. None quantifies predicti... read more 
health informatics

Can synthetic data overcome the privacy and fidelity bottleneck in Pharmacometrics? A comparative benchmark using a daptomycin population pharmacokinetic model

medRxiv Jun 2, 2026
Abstract Introduction The sharing of individual patient data is essential for advancing pharmacometrics but is strictly limited by privacy regulations (e.g., GDPR). While synthetic data generation offers a legally compliant alternative, its structura... read more 
pharmacology and therapeutics

Cost-Effectiveness and Cost-Utility of a Colon Capsule Endoscopy in a Population-Based Screening Program for Colorectal Cancer

medRxiv Jun 2, 2026
Background: Colon capsule endoscopy (CCE) has been proposed as a non-invasive alternative to colonoscopy for colorectal cancer (CRC) screening, offering greater patient comfort and potentially reducing healthcare burden. However, its cost-effectivene... read more 
health policy

Calibrated and Interpretable Machine Learning for ICU Mortality Prediction Using First 24-Hour Clinical Data

medRxiv Jun 2, 2026
Objective: To develop, calibrate, and interpret machine learning models for predicting in-hospital mortality among intensive care unit (ICU) patients using clinical data collected during the first 24 hours of admission. Methods: We analyzed 53,866 ad... read more 
health informatics
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