Artificial Intelligence Medical Compendium

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

Showing 38,971 to 38,980 of 223,469 articles

Bounding Box Anomaly Scoring for simple and efficient Out-of-Distribution detection

arXiv Mar 24, 2026
Out-of-distribution (OOD) detection aims to identify inputs that differ from the training distribution in order to reduce unreliable predictions by deep neural networks. Among post-hoc feature-space approaches, OOD detection is commonly performed by ... read more 
Machine Learning

Large-Scale Avalanche Mapping from SAR Images with Deep Learning-based Change Detection

arXiv Mar 24, 2026
Accurate change detection from satellite imagery is essential for monitoring rapid mass-movement hazards such as snow avalanches, which increasingly threaten human life, infrastructure, and ecosystems due to their rising frequency and intensity. This... read more 
Computer Vision and Pattern Recognition

Large language model scoring of medical student reflection essays: Accuracy and reproducibility of prompt-model variations

medRxiv Mar 24, 2026
Purpose: Evaluate large language models (LLMs) for scoring medical student essays, and compare various prompting techniques and models. Methods: OpenAI GPT scored 51 medical student reflection essays (15 real, 36 fabricated) using a previously-report... read more 
medical education

Structured retrieval closes the gap between low-cost and frontier clinical language models

medRxiv Mar 24, 2026
Most clinical large language model (LLM) benchmarks rely on clean, concise vignettes that do not reflect the noisy, long-form documentation typical of real clinical records. How LLM performance degrades under realistic chart conditions remains poorly... read more 
neurology

Feasibility study on a Noninvasive Assessment of ALS Patient Emotional State

medRxiv Mar 24, 2026
This study addresses the need for objective, real-time assessment of emotional responsiveness and coping strategies in individuals with Amyotrophic Lateral Sclerosis (ALS) to support personalized care. We are using non-invasive speech analysis and da... read more 
neurology

SleepJEPA: Learning the latent world of sleep with at-home sleep data to estimate disease risk

medRxiv Mar 24, 2026
Sleep disturbances lead to risk for cardiovascular (CV), metabolic, and neurological diseases. While in-lab polysomnography (PSG) is the gold standard for measuring sleep disturbances, at-home PSG (hPSG) is increasingly being used and collects a simi... read more 
health informatics

Climate-Informed Deep Learning for Spatio-Temporal Forecasting of Climate-Sensitive Diseases

medRxiv Mar 24, 2026
Effective public health planning and intervention strategies necessitate an understanding of the temporal and geographic distribution of disease incidences. This requires robust frameworks for disease incidence forecasting. However, due to variations... read more 
public and global health

A deep-learning based biomarker of systemic cellular senescence burden to predict mortality and health outcomes

medRxiv Mar 24, 2026
Introduction: The accumulation of senescent cells is a recognized hallmark of biological aging and is associated with the onset of multiple chronic medical conditions. Senescent cells exhibit a distinct secretory profile, known as the senescence-asso... read more 
geriatric medicine

Predicting 5-Year Breast Cancer Risk from Longitudinal Digital Breast Tomosynthesis: A Single-center Retrospective Study

medRxiv Mar 24, 2026
Background: Imaging-based breast cancer risk prediction models primarily use full-field digital mammography (FFDM). As digital breast tomosynthesis (DBT) has become a predominant screening modality in the United States, its potential for long-term br... read more 
radiology and imaging

The Impact of Evaluation Strategy on Sepsis Prediction Model Performance Metrics in Intensive Care Data: Retrospective Cohort Study.

Journal of medical Internet research Mar 24, 2026
BACKGROUND: The prediction of the onset of sepsis, a life-threatening condition resulting from a dysregulated response to an infection, is one of the most common prediction tasks in intensive care-related machine learning research. To assess the perf... read more 
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