Artificial Intelligence Medical Compendium

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

Showing 17,761 to 17,770 of 214,033 articles

Regarding 'artificial intelligence-assisted real-time nasopharyngeal cancer diagnostic model enhances rhinologist performance: a prospective multi-reader study'.

Annals of medicine May 15, 2026
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TIME: A Taylor-Inspired Mixed-Effects Model for IDH Prediction.

IEEE transactions on bio-medical engineering May 15, 2026
BACKGROUND: Intradialytic hypotension (IDH) is a critical complication in hemodialysis that increases morbidity and treatment risks, yet existing machine learning methods inadequately address session-level physiological state heterogeneity and fail t... read more 

Distilling Clinical Reasoning from Text Corpora for Explainable AI in Medical Imaging.

IEEE journal of biomedical and health informatics May 15, 2026
While deep learning models have achieved remarkable diagnostic accuracy in medical imaging, their inherent "black box" nature severely impedes clinical adoption due to a lack of transparency and trust. Current eXplainable AI (XAI) methods, such as sa... read more 

TSGNAS: A Topology- and Semantic-Guided Graph Neural Network Architecture Searcher.

IEEE transactions on neural networks and learning systems May 15, 2026
Designing effective graph neural networks (GNNs) for diverse tasks requires substantial manual effort, especially when dealing with the intricate interplay between topological structures and semantic information in graph data. Existing automated appr... read more 

DSHARP: Deep Incompressible Motion Estimation with Sinusoidal-transformed Harmonic Phase for Tagged MRI.

IEEE transactions on medical imaging May 15, 2026
Tagged magnetic resonance imaging (tMRI) is a valuable tool for visualizing and quantifying tissue deformation in vivo. Its use is often hampered, however, by tag fading, long computation times, and the challenge of ensuring diffeomorphic, incompress... read more 

A Novel Fluoride Tray-Assisted Workflow for AI-driven Automated Maxillary Gingival Segmentation on CBCT.

Dento maxillo facial radiology May 15, 2026
OBJECTIVES: To clinically validate an AI-based tool for automated maxillary gingival segmentation of marginal and supracrestal gingiva on cone beam computed tomography (CBCT) scans using a novel soft tissue separation technique with a fluoride tray. ... read more 

Automated tooth numbering on panoramic radiographs versus cone-beam computed tomographs: A diagnostic accuracy study of a commercial artificial intelligence system.

Dento maxillo facial radiology May 15, 2026
OBJECTIVES: To assess the diagnostic accuracy of a commercial artificial intelligence system for automated tooth numbering on panoramic radiographs and cone-beam computed tomography and to quantify case-level reliability. METHODS: In this retrospecti... read more 

A Multi-Task Deep Learning Model for Quality Control of Periapical Radiographs: Simultaneous Technical Error Classification and Quality Grading.

Dento maxillo facial radiology May 15, 2026
OBJECTIVES: To develop a multi-task deep learning model for the automated quality control of periapical radiographs, integrating identification of technical errors with standardized quality grading. METHODS: A dataset of 3510 periapical radiographs w... read more 

Chrysoprase color grading with machine learning: A systematic approach.

PloS one May 15, 2026
The color of gemstones plays a pivotal role in determining their quality and significantly impacts their market value. However, inconsistencies in gemstone color evaluation, stemming from the subjective nature of color perception, have hindered stand... read more 

Deep learning-based region merging with adaptive threshold optimization for building segmentation in remote sensing images.

PloS one May 15, 2026
Precise extraction of buildings from high-resolution remote sensing images is essential for urban analysis and land management. However, accurately extracting buildings as a region of interest (ROI) from remote sensing (RS) images remains challenging... read more 
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