Artificial Intelligence Medical Compendium

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

Showing 12,001 to 12,010 of 210,314 articles

TriSplat: Simulation-Ready Feed-Forward 3D Scene Reconstruction

arXiv May 25, 2026
Sparse-view 3D reconstruction is increasingly addressed with feed-forward splatting networks that predict explicit primitives directly from images. Yet most existing methods remain centered on Gaussian primitives and expose surfaces only indirectly: ... read more 
Computer Vision and Pattern Recognition

When Rule Violations Are Rare: Chimera Training for Logical Anomaly Detection

arXiv May 25, 2026
Many practical anomalies are not merely rare inputs, but violations of semantic constraints: objects co-occur in structured ways, actions imply preconditions, and events satisfy temporal or relational regularities. We study anomaly detection in this ... read more 
Machine Learning

Co-folding model guided by structural proteomics

arXiv May 25, 2026
Protein structure generative models excel at predicting single protein static structures from sequence, but routinely fail to capture the correct conformational state of protein complexes, critical for protein design and induced proximity modalities ... read more 
Machine Learning cs.AI q-bio.BM

On the Role of Inductive Bias in Time-Series Pretraining: A Case Study in Learning Generalizable Representations for Clinical Time Series

arXiv May 25, 2026
Clinical time-series learning is routinely constrained by small, heterogeneous cohorts and protocol drift, while its downstream use spans both classification (e.g., pathology diagnosis) and regression (e.g., temporal forecasting). These constraints m... read more 
Machine Learning

Artificial intelligence in food technology and processing: a review.

Journal of food science and technology May 25, 2026
UNLABELLED: The food industry faces numerous challenges, including ensuring food safety, managing supply chain disruptions, meeting changing consumer demands, addressing climate change impacts, and reducing food waste. Artificial Intelligence (AI) of... read more 

Normative modeling for quantitative brain MRI phenotyping and biomarker discovery for pediatric leukodystrophies

medRxiv May 25, 2026
Importance: Leukodystrophies are a heterogeneous group of genetic disorders affecting the white matter of the brain, often presenting with overlapping clinical features but differing in neuroanatomical involvement. There is a critical need for quanti... read more 
neurology

Assessing Foundation Models for Computational Pathology in Endometrial Cancer

medRxiv May 25, 2026
Computational pathology leverages deep learning to extract clinically relevant information from digitized tumor slides, predicting histopathological subtypes, molecular alterations, and patient outcomes. Recent pipelines increasingly rely on foundati... read more 
pathology

Cross-Model Variability in Large Language Model Triage Behavior for Potential Stroke Symptoms

medRxiv May 25, 2026
Background: Stroke is a time-sensitive neurological emergency in which early EMS activation and presentation to definitive care are cornerstones of effective therapy. Large language models (LLMs) are increasingly consulted by the public for medical a... read more 
emergency medicine

Cumulative In-Context Learning versus Simple Historical Weighting for Real-Time Geographic Origin Identification of Ongoing Epidemic Waves: A Comparative Evaluation Using Eight COVID-19 Waves in Japan

medRxiv May 25, 2026
Background: Identifying the geographic origin of epidemic waves early is critical for targeted public health responses. Conventional statistical methods for wave origin estimation rely on fixed algorithms applied to case count time-series data and tr... read more 
public and global health

Machine Learning Estimation of Gestational Age at Delivery Using Linked Mother-Infant Electronic Health Records Across Two Health Systems

medRxiv May 25, 2026
Objective This study aimed to train and evaluate supervised machine learning algorithms using electronic health record (EHR) data to accurately estimate gestational age at delivery.
Materials and Methods We trained random forest, gradient boostin... read more 
obstetrics and gynecology
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