Artificial Intelligence Medical Compendium

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

Showing 9,551 to 9,560 of 208,566 articles

MMTC-Net: Multimodal Temporal Cervical Network for HSIL+ Recognition in Precancer Screening.

Journal of imaging informatics in medicine May 27, 2026
Cervical precancer screening is essential for reducing disease-related mortality. In colposcopic practice, clinicians jointly assess dynamic acetic-acid image sequences, iodine-stained images, and structured clinical information when distinguishing H... read more 

DADWMorph: A Global-Local Collaborative Network for Deformable Medical Image Registration.

Journal of imaging informatics in medicine May 27, 2026
Deformable image registration enables spatial alignment across sequential scans for longitudinal disease monitoring, multi-modal fusion in treatment planning, and atlas-based segmentation. Accurate registration supports automated workflows in clinica... read more 

Evaluating Iterative Deep Learning as a Labeling-Efficient Strategy for Tubular Segmentation in Digital Nephropathology.

Journal of imaging informatics in medicine May 27, 2026
Chronic kidney disease (CKD) is a prevalent condition worldwide and a significant global health burden that is expected to increase in the coming decades. Morphological evaluation of renal tubules is critical for diagnosis and prognosis; however, man... read more 

Interpretable Deep Learning Radiomics Model for Preoperative Prediction of High-Grade Soft Tissue Sarcomas: A Multicenter MRI Study.

Journal of imaging informatics in medicine May 27, 2026
This study aims to develop a preoperative fat-suppressed T2-weighted imaging (FS-T2WI)-based deep learning radiomics (DLR) model for predicting high-grade soft tissue sarcomas (STSs). 129 patients from the Cancer Imaging Archive (TCIA) database and o... read more 

A stacked multi-classifier for multi-modal data fusion in transcranial sonography-based Parkinson's disease assessment.

NPJ Parkinson's disease May 27, 2026
Parkinson's disease (PD) is a catastrophic neurodegenerative disorder and a major culprit of neurological disability worldwide. Accurate diagnosis of PD, especially in its early stages, is paramount for timely intervention and effective therapeutic m... read more 

EnzymeTuning improves enzyme-constrained metabolic modeling and proteome abundance prediction through deep learning.

Nature communications May 27, 2026
The accuracy of enzyme kinetic parameters, particularly enzyme turnover numbers (kcat), is critical for the predictive performance of enzyme-constrained genome-scale metabolic models. However, currently available kinetic datasets remain sparse and of... read more 

A hybrid transformer-zero-shot learning framework with Muon optimization for intelligent channel estimation in MIMO wireless systems.

Scientific reports May 27, 2026
For MIMO wireless systems, accurate channel estimation is essential. However, traditional and current Deep Learning (DL) techniques have poor generalization to unknown situations and necessitate repeated retraining. For intelligent MIMO channel estim... read more 

In-vivo iron mapping in patients with Parkinson's disease using deep learning-based susceptibility source separation MRI.

NPJ Parkinson's disease May 27, 2026
Parkinson's disease (PD) involves pathological iron accumulation, yet MRI metrics, such as R2* or magnetic susceptibility (χ), lack mechanistic specificity because they convolve paramagnetic and diamagnetic sources. We applied an AI-assisted χ-separa... read more 

A Multi-center Gadolinium-ethoxybenzyl-diethylenetriamine Pentaacetic Acid (Gd-EOB-DTPA) MRI Dataset with Expert Annotations and clinicopathological data.

Scientific data May 27, 2026
Liver resection is a cornerstone treatment for liver tumors, yet post-hepatectomy liver failure (PHLF) remains a severe and life-threatening complication with no effective treatment. Recent advances in artificial intelligence (AI) have shown promise ... read more 

A federated deep learning framework with distributed hybrid character-level and attention mechanisms for scalable and cost-efficient fake news detection.

Scientific reports May 27, 2026
Fake news detection is an essential task for media and news organizations to maintain the trust and reliability of the published content. Due to the rapid growth of online users and the spread of misinformation through malicious sources, the fake new... read more 
Popular Topics
Recent Journals