Artificial Intelligence Medical Compendium

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

Showing 53,041 to 53,050 of 225,548 articles

Developing and validating a machine learning model for predicting post-thrombolysis seizures in acute ischemic stroke.

Medicine Feb 6, 2026
Post-stroke seizures (PSS) manifests variably due to ischemic brain injury, yet its risk factors remain unclear. This study developed a machine learning (ML) model using clinical and laboratory data to predict PSS risk in acute ischemic stroke (AIS) ... read more 

Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: A cross-sectional SHAP-based analysis of NHANES 2009-2023.

Medicine Feb 6, 2026
Depression (DEP) is a common yet underdiagnosed comorbidity in adults with type 2 diabetes mellitus (T2DM), worsening glycemic control and increasing complication risk. Practical, interpretable risk tools using routine patient data are limited. We co... read more 

Data-driven predictive modeling for massive intraoperative blood loss during living donor liver transplantation: Integrating machine learning techniques.

PloS one Feb 6, 2026
BACKGROUND: Massive intraoperative bleeding (IBL) in liver transplantation (LT) poses serious risks and strains healthcare resources necessitating better predictive models for risk stratification. As traditional models often fail to capture the compl... read more 

Giving AI agents a sense of control facilitates reinforcement learning in multitasking scenarios.

PloS one Feb 6, 2026
Having to control multiple tasks in parallel poses challenges for humans and artificial agents alike. In artificial intelligence, specific forms of reinforcement learning (RL), most notably hierarchical and model-based RL, have shown promising result... read more 

Perceived Potential and Challenges of Supporting Coronary Artery Disease Treatment Decisions With AI: Qualitative Study.

JMIR cardio Feb 6, 2026
BACKGROUND: Coronary revascularization decision-making for patients with coronary artery disease (CAD) can be complex and challenging. Artificial intelligence (AI) has the potential to improve this decision-making by bringing data-driven insights to ... read more 

Machine learning-inspired similarity measure to forecast M&A from patent data.

PloS one Feb 6, 2026
Defining and finalizing Mergers and Acquisitions (M&A) requires complex human skills, which makes it very hard to automatically find the best partner or predict which firms will make a deal. In this work, we propose the MASS algorithm, which adapts a... read more 

Carbon-phosphorus exchange rate constrains density-speed trade-off in arbuscular mycorrhizal fungal growth.

Proceedings of the National Academy of Sciences of the United States of America Feb 6, 2026
Symbiotic nutrient exchange between arbuscular mycorrhizal (AM) fungi and their host plants varies widely depending on their physical, chemical, and biological environment. Yet dissecting this context dependency remains challenging because we lack me... read more 

Probabilistic mapping and automated segmentation of human brainstem white matter bundles.

Proceedings of the National Academy of Sciences of the United States of America Feb 6, 2026
Brainstem white matter (WM) bundles are essential conduits for neural signals that modulate homeostasis and consciousness. Their architecture forms the anatomic basis for brainstem connectomics, subcortical circuit models, and deep brain navigation t... read more 

Order parameters and phase transitions of continual learning in deep neural networks.

Proceedings of the National Academy of Sciences of the United States of America Feb 6, 2026
Continual learning (CL) enables animals to learn new tasks without erasing prior knowledge. CL in artificial neural networks (NNs) is challenging due to catastrophic forgetting, where new learning degrades performance on older tasks. While various te... read more 

Identifying genome-by-childhood trauma interactions for depression using a forest-based approach in the UK Biobank and Adolescent Brain Cognitive Development Study.

Proceedings of the National Academy of Sciences of the United States of America Feb 6, 2026
Depression is shaped by both genetic and environmental factors, but genome-wide interaction studies (GWIS) often lack power to detect complex gene-environment (G × E) interactions. We applied a forest-based machine learning approach to 38,018 UK Biob... read more 
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