Artificial Intelligence Medical Compendium

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

Showing 58,781 to 58,790 of 227,634 articles

Technical Acquisition Parameters Dominate Demographic Factors in Chest X-ray AI Performance Disparities: A Multi-Dataset External Validation Study

medRxiv Jan 22, 2026
Artificial intelligence systems for chest radiograph interpretation are increasingly deployed in clinical practice, yet current fairness frameworks emphasize demographic subgroup analysis while the relative contribution of technical acquisition param... read more 
radiology and imaging

Predicting the need for medical care after toxin exposure using SHAP-interpretable gradient boosting

medRxiv Jan 22, 2026
Objective: Experts in poison control centers must accurately and efficiently assess the severity of an exposure, neither delaying care nor pointlessly sending patients to the hospital, using only the information given during a first phone call. To he... read more 
toxicology

Integrating Quantitative Histology with Clinical Data Improves Prediction of Cervical Intraepithelial Neoplasia Regression

medRxiv Jan 22, 2026
Cervical intraepithelial neoplasia grade 2 (CIN2) lesions show variable outcomes, and accurate prediction of regression remains a major clinical challenge. We developed an interpretable machine learning pipeline that integrates quantitative histologi... read more 
obstetrics and gynecology

I3LUNG: Clinical Validation of a Multimodal AI Tool to Support Immunotherapy Decisions in NSCLC

medRxiv Jan 22, 2026
Despite a decade of immunotherapy, treatment selection in non-small cell lung cancer (NSCLC) still relies on subgroup analyses and clinical scores. I3LUNG (NCT05537922) is currently the largest international, real-world, multimodal, artificial intell... read more 
oncology

Retrospective multi-cohort validation of a real-world transcriptomics-guided machine learning model for treatment response prediction in breast cancer

medRxiv Jan 22, 2026
Selection of systemic therapy for breast cancer remains largely empirical, particularly for chemotherapy, due to the lack of robust biomarkers that predict treatment response at the individual patient level. We developed Oncology CoPilot, a real-worl... read more 
oncology

Analyzing Neural Network Information Flow Using Differential Geometry

arXiv Jan 22, 2026
This paper provides a fresh view of the neural network (NN) data flow problem, i.e., identifying the NN connections that are most important for the performance of the full model, through the lens of graph theory. Understanding the NN data flow provid... read more 
Machine Learning cs.SC

Experience with Single Domain Generalization in Real World Medical Imaging Deployments

arXiv Jan 22, 2026
A desirable property of any deployed artificial intelligence is generalization across domains, i.e. data generation distribution under a specific acquisition condition. In medical imagining applications the most coveted property for effective deploym... read more 
Image and Video Processing cs.AI cs.CV cs.LG

Superpixel-Based Image Segmentation Using Squared 2-Wasserstein Distances

arXiv Jan 22, 2026
We present an efficient method for image segmentation in the presence of strong inhomogeneities. The approach can be interpreted as a two-level clustering procedure: pixels are first grouped into superpixels via a linear least-squares assignment prob... read more 
Computer Vision and Pattern Recognition math.PR

Coarse-to-Fine Non-rigid Multi-modal Image Registration for Historical Panel Paintings based on Crack Structures

arXiv Jan 22, 2026
Art technological investigations of historical panel paintings rely on acquiring multi-modal image data, including visual light photography, infrared reflectography, ultraviolet fluorescence photography, x-radiography, and macro photography. For a co... read more 
Computer Vision and Pattern Recognition

DSGym: A Holistic Framework for Evaluating and Training Data Science Agents

arXiv Jan 22, 2026
Data science agents promise to accelerate discovery and insight-generation by turning data into executable analyses and findings. Yet existing data science benchmarks fall short due to fragmented evaluation interfaces that make cross-benchmark compar... read more 
Artificial Intelligence
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