Artificial Intelligence Medical Compendium

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

Showing 6,141 to 6,150 of 205,623 articles

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

Enhanced precision of tensor electrocardiography through increased cumulative distribution function resolution: Validation in healthy individuals

medRxiv Jun 2, 2026
Deep-learning ECG analysis is advancing rapidly but lacks stable, physiologically interpretable indicators to anchor explainable artificial intelligence (AI). Tensor cardiography (TCG) models electrocardiographic (ECG) waveforms as differences betwee... read more 
cardiovascular medicine

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

Augmenting Structured Diagnoses through Effective Use of Pre-trained Large Language Models on Clinical Notes

medRxiv Jun 2, 2026
Objective Clinical narrative provides a unique window into provider reasoning and attribution, but use has been limited by resource requirements and extensive fine-tuning, and LLMs in particular have traditionally not performed well at medical coding... read more 
health informatics

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

Mitigating Automation Bias in Physician-LLM Diagnostic Reasoning Using Behavioral Nudges: A Randomized Controlled Trial

medRxiv Jun 2, 2026
As large language models (LLMs) enter clinical workflows, automation bias, the uncritical acceptance of automated output, poses a patient-safety risk. Optimal physician-AI collaboration requires trust calibration, matching scrutiny to LLM recommendat... read more 
health informatics

SchistoTrackVideoNet: multilabel deep learning-based classification of schistosomal periportal fibrosis from ultrasound video

medRxiv Jun 2, 2026
Schistosomiasis causes a complex, difficult to diagnose form of liver fibrosis with high rates of life-threatening morbidity in resource-poor settings where there are often no trained sonographers. Protocols for diagnosis of schistosomiasis-related l... read more 
infectious diseases

Neovascular Glaucoma at a Tertiary Centre in Finland, 2008-2024: A Retrospective Cohort Study

medRxiv Jun 2, 2026
Background/Aims: Neovascular glaucoma (NVG) is an aggressive secondary glaucoma with limited longitudinal data. This study reports the aetiologies, treatments, and longitudinal outcomes in NVG. Methods: Patients with NVG were identified through elect... read more 
ophthalmology

SchistoTrackNet: machine learning for diagnosis of schistosomiasis-associated periportal fibrosis from ultrasound images

medRxiv Jun 2, 2026
Liver fibrosis is a major cause of death in low- and middle-income country contexts. In rural, poor areas of sub-Saharan Africa, schistosomiasis is an underestimated cause of liver fibrosis. Despite the need for increased diagnostic capacity for schi... read more 
infectious diseases

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
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