Artificial Intelligence Medical Compendium

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

Showing 56,341 to 56,350 of 226,846 articles

A New Insight into Imaging Diagnosis of Otosclerosis Enhanced by Machine Learning and Radiomics.

Journal of imaging informatics in medicine Jan 30, 2026
Otosclerosis is a disease affecting the middle and inner ear, characterized by abnormal bone remodeling that leads to stapes fixation and progressive hearing loss. Although high-resolution computed tomography (HRCT) is the standard imaging modality f... read more 

Artificial intelligence-driven 3D surface-topography app for screening and monitoring adolescent scoliosis: early results from a single institution.

Spine deformity Jan 30, 2026
PURPOSE: Radiation-free tools, such as scoliometers, ultrasound, and Moiré topography, have been explored for monitoring Adolescent Idiopathic Scoliosis (AIS), but none have replaced the need for serial spinal radiographs. This study aimed to evaluat... read more 

Deep learning for early diagnosis of uveal melanoma: a systematic review and meta-analysis.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico Jan 30, 2026
BACKGROUND: Uveal melanoma (UM) is a rare cancer with an estimated annual incidence of 6 incidences per million people. About half of UM patients develop distant metastases, mainly to the liver. After metastasis, prognosis is poor, with median surviv... read more 

Machine learning assisted masking of parasitic signals in Bragg coherent diffraction imaging.

Journal of synchrotron radiation Jan 30, 2026
Bragg coherent diffraction imaging (BCDI) is a lens-less technique capable of imaging the strain in a particle in the size range from 20 nm up to several micrometres. This indirect measurement technique, used in X-ray synchrotrons or free-electron la... read more 

Fe metal-organic framework-derived heterojunction for metabolic diagnosis of thymic epithelial tumor.

Proceedings of the National Academy of Sciences of the United States of America Jan 30, 2026
Thymic epithelial tumors (TETs), rare yet clinically significant malignancies, face diagnostic challenges due to their occult presentation and lack of noninvasive risk-stratification tools, leading to systemic overtreatment and poor prognoses for hig... read more 

Uralenol, Glycyrol, and Abyssinone II as potent inhibitors of fibroblast growth factor receptor 2 from anti-cancer plants: A deep learning and molecular dynamics approach.

PloS one Jan 30, 2026
Fibroblast Growth Factor Receptor 2 (FGFR2) plays a critical role in cellular proliferation and differentiation, and its dysregulation is associated with multiple cancers. This study integrates molecular docking, deep learning, pharmacokinetic profil... read more 

Graph former-CL: A novel graph transformer with contrastive learning framework for enhanced drug-drug interaction prediction.

PloS one Jan 30, 2026
Drug-drug interactions (DDI) represent a significant clinical challenge in modern healthcare, contributing to over 125,000 deaths annually in the United States alone. Current computational approaches face substantial limitations in capturing long-ran... read more 

An interpretable machine learning framework for adverse drug reaction prediction from drug-target interactions.

PloS one Jan 30, 2026
BACKGROUND: Adverse drug reactions (ADRs) present challenges to patient safety and healthcare systems. Current pharmacovigilance methods, such as the Yellow Card Scheme (YCS), provide valuable post-marketing data, but the mechanistic causes of these ... read more 

Hierarchy and hope: Exploring AI's role in medicine through a thematic analysis of online discourse.

PLOS digital health Jan 30, 2026
The healthcare community remains divided on the benefits of artificial intelligence (AI) in medicine. In this qualitative study, we sought to better understand the perceived opportunities and threats of AI among premedical students, medical students,... read more 

DOSTA-Net: Domain-Shuffle Temporal Attention Network for Vessel Extraction in X-Ray Coronary Angiography Using Synthetic Data.

IEEE transactions on medical imaging Jan 30, 2026
Artery extraction from X-ray coronary angiography (XCA) images is essential for the accurate diagnosis and treatment of coronary artery diseases. However, vessel visibility is significantly obscured by superimposed fluoroscopic densities from bones a... read more 
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