Artificial Intelligence Medical Compendium

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

Showing 65,701 to 65,710 of 232,257 articles

Latest research

Beyond the Cell Atlas: Functional Communities as the Essential Pathologic Units Driving Kidney Disease.

Journal of the American Society of Nephrology : JASN Jan 9, 2026
Kidney disease represents a growing global health crisis, demanding a deeper understanding of its underlying pathophysiology. Current mechanistic efforts are often focused on discrete cell states identified by single-cell sequencing, which remains th... read more 

Author's Reply: Unrecognized Biases and Validation Gaps in TraceOrg for Automated Autosomal Dominant Polycystic Kidney Disease Volumetry.

Journal of the American Society of Nephrology : JASN Jan 9, 2026
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Unrecognized Biases and Validation Gaps in TraceOrg for Automated Autosomal Dominant Polycystic Kidney Disease Volumetry.

Journal of the American Society of Nephrology : JASN Jan 9, 2026
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Unveiling sodium storage mechanisms in hard carbon via machine learning-driven simulations integrated with accurate site occupation identification.

Chemical science Jan 9, 2026
Hard carbon (HC) has attracted considerable interest as a promising anode material for sodium-ion batteries (SIBs) due to its high specific capacity, excellent cycling stability, and cost-effectiveness. Nevertheless, the sodium storage mechanism in H... read more 

Machine learning-based multi-class classification of bladder pathologies using fused 3D CT radiomic and 3D auto-encoder deep features.

European journal of radiology open Jan 9, 2026
OBJECTIVE: To develop an automated analytical framework that integrates hybrid radiomics and deep learning features from non-contrast CT images for the multi-class classification of bladder pathologies. METHODS: This retrospective study analyzed 902 ... read more 

Predicting Occlusion Myocardial Infarctions in the Emergency Department Using Artificial Intelligence.

Journal of the American College of Emergency Physicians open Jan 9, 2026
OBJECTIVES: The objective was to develop an artificial intelligence (AI) model for predicting acute coronary occlusion myocardial infarction (OMI) in patients with chest pain at the emergency department (ED), using information that is widely availabl... read more 

Efficient multi-agent communication via entity-aware causal network.

Neural networks : the official journal of the International Neural Network Society Jan 9, 2026
Communication is considered as a crucial approach for solving complicated multi-agent reinforcement learning (MARL) cooperative tasks. However, existing approaches rely on predefined agent orders and identifiers to learn targeted communication. The p... read more 

MLGO: Multi-Layer graph neural ODEs for traffic forecasting.

Neural networks : the official journal of the International Neural Network Society Jan 9, 2026
Spatial-temporal graph neural networks have become increasingly prominent in traffic forecasting, driven by the inherently graph-structured nature of traffic networks. While temporal dependencies have been extensively studied, spatial correlations re... read more 

Point-Deeponet: Predicting nonlinear fields on non-Parametric geometries under variable load conditions.

Neural networks : the official journal of the International Neural Network Society Jan 9, 2026
Nonlinear structural analyses in engineering often require extensive finite element simulations, limiting their applicability in design optimization and real-time control. Conventional deep learning surrogates often struggle with complex, non-paramet... read more 

ReTri: Progressive domain bridging via representation disentanglement and triple-level consistency-driven feature alignment for unsupervised domain adaptive medical image segmentation.

Neural networks : the official journal of the International Neural Network Society Jan 9, 2026
Unsupervised domain adaptation (UDA) in medical image segmentation presents significant challenges due to substantial cross-domain disparities and the inherent absence of target domain annotations. In this study, to address these challenges, we propo... read more 

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