Artificial Intelligence Medical Compendium

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

Showing 36,741 to 36,750 of 223,469 articles

Contrastive Learning Model for Wearable-Based Ataxia Assessment.

IEEE transactions on bio-medical engineering Apr 1, 2026
OBJECTIVE: Frequent and objective assessment of ataxia severity is essential for tracking disease progression and evaluating the effectiveness of potential treatments. Wearable-based assessments have emerged as a promising solution. However, existing... read more 

OPTIMUS: Predicting Multivariate Outcomes in Alzheimer's Disease Using Multi-Modal Data Amidst Missing Values.

IEEE transactions on bio-medical engineering Apr 1, 2026
OBJECTIVE: Alzheimer's disease, a progressive neurodegenerative disorder, involves neural, genetic, and proteomic factors and impacts multiple cognitive and behavioral domains. Traditional AD prediction largely focuses on univariate disease outcomes,... read more 

Annular Prior Prompt Learning for Medical Images Segmentation.

IEEE transactions on bio-medical engineering Apr 1, 2026
Excellent performance has been achieved on medical image segmentation. Still, existing algorithms perform relatively poorly for annular objects with high intra-class variability and inter-class similarity, which easily leads to regional confusion, es... read more 

Patient-Specific Cardio-Respiratory Model for Optimization of Cardiac Radioablation.

IEEE transactions on bio-medical engineering Apr 1, 2026
Stereotactic Arrhythmia Radioablation (STAR) is a promising treatment for refractory ventricular tachycardia. However, its precision may be hampered by cardiac and respiratory motions. Multiple techniques exist to mitigate the effects of these displa... read more 

Diffusion-QSM: Diffusion Model With Time-Travel and Resampling Refinement for Quantitative Susceptibility Mapping.

IEEE transactions on bio-medical engineering Apr 1, 2026
OBJECTIVE: Quantitative susceptibility mapping (QSM) is a useful magnetic resonance imaging technique. We aim to propose a deep learning (DL)-based method for QSM reconstruction that is robust to data perturbations. METHODS: We developed Diffusion-QS... read more 

Self-Supervised Learning With Adaptive Graph Modeling for EEG-Based Epileptic Seizure Classification.

IEEE transactions on bio-medical engineering Apr 1, 2026
OBJECTIVE: Epileptic seizure classification using EEG signals remains a significant challenge due to complex spatial-temporal dependencies, limited labeled data, and severe class imbalance. METHODS: We propose a self-supervised learning framework, AS... read more 

Advancing Point-of-Care Still's Murmur Identification: Evaluating the Efficacy of ConvNets and Transformers Using the StethAid Multicenter Heart Sound Database.

IEEE transactions on bio-medical engineering Apr 1, 2026
BACKGROUND: Primary care providers (PCPs) are not successful in accurately identifying Still's murmur with no available clinical tools to aid in the process. Existing deep learning (DL) methods primaryly focused on adult pathological murmurs or murmu... read more 

Geometric-Driven Cross-Modal Registration Framework for Optical Scanning and CBCT Models in AR-Based Maxillofacial Surgical Navigation.

IEEE transactions on bio-medical engineering Apr 1, 2026
OBJECTIVE: Accurate preoperative planning for dental implants, especially in edentulous or partially edentulous patients, relies on precise localization of radiographic templates that guide implant positioning. By wearing a patient-specific radiograp... read more 

MUSiK: An Open Source Simulation Library for 3D Multi-View Ultrasound.

IEEE transactions on bio-medical engineering Apr 1, 2026
Diagnostic ultrasound has long filled a crucial niche in medical imaging thanks to its portability, affordability, and favorable safety profile. Now, multi-view hardware and deep-learning-based image reconstruction algorithms promise to extend this n... read more 

Generative AI Empower Addiction-Related Brain Circuits Detection via Graph Diffusion-Infused Adversarial Learning.

IEEE transactions on cybernetics Apr 1, 2026
The study of the nicotine addiction mechanism is of great significance in both nicotine withdrawal and brain science. The detection of addiction-related brain circuitry using functional magnetic resonance imaging (fMRI) is a critical step in studying... read more 
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