Artificial Intelligence Medical Compendium

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

Showing 27,691 to 27,700 of 218,939 articles

Recovering Clinical Detail in AI-Generated Responses for Low Back Pain Through Prompt Design

medRxiv Apr 23, 2026
Introduction Large language models are increasingly being used in healthcare. In interventional pain medicine, clinical reasoning is essential for procedural planning. Prior studies show that simplified prompts reduce clinical detail in AI-generated ... read more 
pain medicine

Predicting Depressive Symptoms Among Reproductive-Aged Women in Bangladesh Using Bagging Ensemble Machine Learning on Imbalanced Bangladesh Demographic and Health Survey 2022 Data

medRxiv Apr 23, 2026
Background Depressive symptoms among reproductive-aged women represent a major public health concern in low- and middle-income countries, yet systematic screening remains limited. In most population survey datasets, the low prevalence of depression r... read more 
public and global health

Assessing medication-related burden and medication adherence among older patients from Central Nepal: A machine learning approach

medRxiv Apr 23, 2026
We are pleased to submit our Original article entitled "Assessing medication-related burden and medication adherence among older patients from Central Nepal: A machine learning approach" for consideration in your esteemed journal. In this paper, we a... read more 
geriatric medicine

Accessible and Reproducible Renal Cell Carcinoma Research Through Open-Sourcing Data and Annotations

medRxiv Apr 23, 2026
Background: Medical imaging, especially computed tomography and magnetic resonance imaging, is essential in clinical care of patients with renal cell carcinoma (RCC). Artificial intelligence (AI) research into computer-aided diagnosis, staging and tr... read more 
radiology and imaging

CohortContrast: An R Package for Enrichment-Based Identification of Clinically Relevant Concepts in OMOP CDM Data

medRxiv Apr 23, 2026
Abstract Objective To address the unresolved bottleneck of selecting cohort-relevant clinical concepts for treatment trajectory analysis in observational health data, we introduce CohortContrast, an OMOP-compatible R package for enrichment-based conc... read more 
health informatics

Liver Biomarker Improves AHA/ACC 10-year ASCVD Risk Prediction in US and China Cohorts with ML

medRxiv Apr 23, 2026
Introduction: Accurate stratification of hard atherosclerotic cardiovascular disease (ASCVD) risk remains challenging despite advances in prevention. Liver function biomarkers (LFBs), particularly gamma - glutamyl transferase (GGT), have been linked ... read more 
cardiovascular medicine

Patient perspectives on living with hypertension: Social media listening analysis across predominantly high-income countries

medRxiv Apr 23, 2026
Background: Chronic conditions such as hypertension can significantly disrupt daily life and emotional wellbeing. The interaction between patients' perceptions, adherence to antihypertensive medication and quality of life (QoL) remains underexplored ... read more 
cardiovascular medicine

Dissecting clinical reasoning failures in frontier artificial intelligence using 10,000 synthetic cases

medRxiv Apr 23, 2026
Background: Current medical large language model (LLM) evaluations largely rely on small collections of cases, whereas rigorous safety testing requires large-scale, diverse, and complex cases with verifiable ground truth. Multiple Sclerosis (MS) prov... read more 
neurology

A Cross-Cohort Validated Plasma Lipid Biomarker Assay for Early Breast Cancer Detection Using Machine Learning

medRxiv Apr 23, 2026
Early detection of breast cancer remains essential for improving clinical outcomes, and complementary non-invasive approaches are needed to support existing screening methods, particularly for women with dense breast tissue. We have previously report... read more 
oncology

Comparative Evaluation of Deep Learning Models for 3D Segmentation and Volumetry of Vestibular Schwannomas Using Large Heterogeneous Data Sets with External Validation.

AJNR. American journal of neuroradiology Apr 23, 2026
BACKGROUND AND PURPOSE: 3D segmentation and volumetry of vestibular schwannomas (VSs) is a more accurate method to determine tumor growth on serial imaging, but manual annotation is time-consuming to implement in routine clinical practice. We evaluat... read more 
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