Artificial Intelligence Medical Compendium

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

Showing 55,781 to 55,790 of 226,731 articles

Design, Modeling and Evaluation of Lattice Structure Pneumatic Actuators (LSPAs) for Soft Wrist Rehabilitation Robot.

IEEE transactions on bio-medical engineering Feb 1, 2026
Soft robots have gained recognition as promising solutions in rehabilitation robotics due to their intrinsic flexibility and safety features. However, they often encounter challenges related to output efficiency and portability. This paper presents t... read more 

The Second Skin: A Wearable Sensor Suite That Enables Real-Time Human Biomechanics Tracking Through Deep Learning.

IEEE transactions on bio-medical engineering Feb 1, 2026
OBJECTIVE: Real-time determination of human kinematics and kinetics could advance biomechanics research and enable valuable applications of biofeedback and generalizable exoskeleton control. This work aims to investigate a task-independent, user-inde... read more 

BDEC: Brain Deep Embedded Clustering Model for Resting State fMRI Group-Level Parcellation of the Human Cerebral Cortex.

IEEE transactions on bio-medical engineering Feb 1, 2026
OBJECTIVE: To develop a robust group-level brain parcellation method using deep learning based on resting-state functional magnetic resonance imaging (rs-fMRI), aiming to release the model assumptions made by previous approaches. METHODS: We proposed... read more 

Knowledge-Augmented Patient Network Embedding-Based Dynamic Model Selection for Predictive Analysis of Pediatric Drug-Induced Liver Injury.

IEEE transactions on bio-medical engineering Feb 1, 2026
OBJECTIVE: To address the challenges of developing machine learning frameworks for Electronic Health Records (EHRs)-based predictive tasks, such as the intricate occurrence mechanism of clinical events, patient diversity, and the inherent limitations... read more 

Explainable Temporal Inference for Irregular Multivariate Time Series. A Case Study for Early Prediction of Multidrug Resistance.

IEEE transactions on bio-medical engineering Feb 1, 2026
OBJECTIVE: Many healthcare problems involve complex patient trajectories represented as Multivariate Time Series (MTS), with predictions often coming as Time Series (TS) outputs. Despite recent advances, these "MTS-to-TS" inference tasks remain chall... read more 

Predicting Traumatic Brain Injury Post-Trauma Using Temporal Attention on Sleep-Wake Data.

IEEE transactions on bio-medical engineering Feb 1, 2026
BACKGROUND: Traumatic Brain Injury (TBI) is a major public health concern, and accurate classification is essential for effective treatment and improved patient outcomes. Sleep/wake behavior has emerged as a potential biomarker for TBI classification... read more 

Assignment of the Biological Identity of Breast Masses in Contrast-enhanced Spectral Computed Tomography Examinations of Chest Carried Out in Clinical Routine Diagnostics.

Investigative radiology Feb 1, 2026
BACKGROUND: Focal breast lesions are observed in up to 5.8% of CT examinations performed in female patients for a wide variety of indications not affecting the breast. To simplify and standardize the further procedure in the case of breast masses vis... read more 

FedEMG: Achieving Generalization, Personalization, and Resource Efficiency in EMG-Based Upper-Limb Rehabilitation Through Federated Prototype Learning.

IEEE transactions on bio-medical engineering Feb 1, 2026
Upper extremity amputation, often necessitated by traumatic injuries, significantly impacts an individual's well-being. This paper addresses the critical challenges of deploying deep learning for real-time electromyography-based gesture recognition i... read more 

AI-Driven Electrographic Seizure Classification and Seizure Onset Detection Using Image- and Time-Series-Based Approaches.

IEEE transactions on bio-medical engineering Feb 1, 2026
OBJECTIVE: Manually distinguishing between seizure and non-seizure events in intracranial electroencephalography (iEEG) recordings is highly time-consuming. In this study, we explored AI-based approaches for electrographic seizure classification (ESC... read more 

Graph Convolutional Networks Enable Fast Hemorrhagic Stroke Monitoring With Electrical Impedance Tomography.

IEEE transactions on bio-medical engineering Feb 1, 2026
OBJECTIVE: To develop a fast image reconstruction method for stroke monitoring with electrical impedance tomography with image quality comparable to computationally expensive nonlinear model-based methods. METHODS: A post-processing approach with gra... read more 
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