Artificial Intelligence Medical Compendium

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

Showing 591 to 600 of 200,021 articles

A comparison of vendor artificial intelligence solutions for automated post-processing of short-axis cine images in cardiovascular magnetic resonance imaging.

Scientific reports Jun 2, 2026
Automated segmentation of cardiac magnetic resonance (CMR) imaging is integrated into clinical workflows, yet comparative performance across vendor AI solutions remains insufficiently characterized. This study assessed three models (two commercial, o... read more 

Predicting diffusion-FLAIR mismatch from B1000 and ADC without FLAIR: A deep learning-based approach.

Scientific reports Jun 2, 2026
Diffusion-FLAIR mismatch (DFM), defined as the discrepancy between diffusion-weighted imaging (DWI) and FLAIR sequences, is a key imaging biomarker used to identify patients with unclear symptom onset or those likely to benefit from recanalization th... read more 

Modeling the interpretable geometric-performance relationship of metamaterials on small datasets using Kolmogorov-Arnold operator informed network.

Scientific reports Jun 2, 2026
Deep learning has been extensively employed in the prediction of metamaterial properties. However, the multi-layer perceptron-kernelled methods lack interpretability and are highly dependent on large datasets, making the end-to-end mapping opaque and... read more 

Clinical determinants of retinal age gap estimated from fundus photographs in glaucoma patients.

Scientific reports Jun 2, 2026
Retinal age gap (RAG), defined as the difference between artificial intelligence-predicted retinal age and chronological age derived from fundus photographs, has been proposed as a potential biomarker of biological aging; however, the influence of oc... read more 

Uncertainty-aware spatio-temporal contrastive graph neural networks for cyber financial fraud detection and risk management.

Scientific reports Jun 2, 2026
Financial fraud detection requires screening massive transaction networks where evolving topologies, extreme label sparsity, and asymmetric misclassification costs make traditional classification paradigms ineffective. We propose ST-CGNN, a spatio-te... read more 

A Promptable 3D-CT Foundation Model-Based Approach for Pulmonary Embolism.

Cardiovascular and interventional radiology Jun 2, 2026
PURPOSE: Blood clot volume (BCV), defined as the total three-dimensional (3D) volume of the thrombus on computed tomography angiography (CTA), is an objective biomarker of pulmonary embolism (PE) severity whose clinical use is limited by time-consumi... read more 

Potential of machine learning for prevention and control of neglected tropical diseases: a scoping review.

Communications medicine Jun 2, 2026
BACKGROUND: Neglected Tropical Diseases disproportionately affect populations in Africa and other low- and middle-income countries. Machine learning has potential to improve disease prediction, detection and control, but its use in neglected tropical... read more 

A multi-scale supervised contrastive framework for cross-domain soybean disease classification using leaf and UAV imagery.

Scientific reports Jun 2, 2026
Accurate and scalable soybean crop health monitoring remains a major challenge in precision agriculture due to environment variability, inconsistent lighting conditions, and significant differences between the ground-level leaf imagery and UAV-based ... read more 

Metab8D: a metabolic regulome network from multiomics and machine learning.

Communications biology Jun 2, 2026
To explore multiomic regulation of the metabolome, we used machine learning to predict metabolomic variation across ~1000 different cancer cell lines with matched omics data from eight biomolecular classes: genomic copy number variation, mutations, D... read more 

Digital Transformation of Medicines Regulation in Africa-Perspectives from a Stakeholder Convening.

Clinical pharmacology and therapeutics Jun 2, 2026
Regulatory authorities worldwide are developing strategies to integrate artificial intelligence (AI) into the lifecycle of health products, technologies, and medicines. While regulators share goals of improving efficiency, strengthening decision-maki... read more 
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