Artificial Intelligence Medical Compendium

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

Showing 7,191 to 7,200 of 206,272 articles

A Cost-Efficient Multi-Angle Fusion Deep Learning for Ultrasound Localization Microscopy.

IEEE transactions on bio-medical engineering Jun 1, 2026
Ultrasound localization microscopy (ULM) enables super-resolution imaging of microvascular structures by localizing microbubbles from clutter-filtered ultrafast ultrasound data. However, conventional clutter filtering methods, particularly those base... read more 

FOSTER: A Comprehensive Pipeline for Transabdominal Fetal Pulse Oximetry Validated in a Large Animal Model of Pregnancy.

IEEE transactions on bio-medical engineering Jun 1, 2026
OBJECTIVE: Transabdominal fetal pulse oximetry (TFO) has the potential to supplement present intrapartum fetal monitoring approaches, which cannot accurately detect fetuses at risk of birth asphyxia. However, non-invasive measurement of fetal oxygen ... read more 

Zero-Shot Unsupervised Motion Estimation for Motion-Corrected Cardiac T1 Mapping.

IEEE transactions on bio-medical engineering Jun 1, 2026
OBJECTIVE: Cardiac quantitative MRI (qMRI) is a powerful imaging technique for diagnosing pathologies such as diffuse myocardial fibrosis. One main challenge is cardiac motion, which requires synchronization of data acquisition with the heartbeat, le... read more 

High Sensitivity Sensor Based on Bound State in the Continuum in Detection for Cancer Cells.

IEEE transactions on bio-medical engineering Jun 1, 2026
Although terahertz (THz) metasurfaces based on bound state in the continuum (BIC) have garnered significant attention in biomedical applications, their technical implementation in high-sensitivity cancer cells detection remains a critical challenge. ... read more 

Unsupervised Cross-Modality MR Image Segmentation via Prompt-Driven Foundation Model.

IEEE transactions on bio-medical engineering Jun 1, 2026
Obtaining pixel-level expert annotations is expensive and labor-intensive in the medical imaging field, especially for multi-modality imaging data like MR. Most conventional cross-modality segmentation methods rely on unsupervised domain adaptation t... read more 

An Active Dry-Contact Continuous EEG Monitoring System for Seizure Detection Applications in Clinical Neurophysiology.

IEEE transactions on bio-medical engineering Jun 1, 2026
OBJECTIVE: Young children and infants, especially newborns, are highly susceptible to seizures, which, if undetected and untreated, can lead to severe long-term neurological consequences. Early detection typically requires continuous electroencephalo... read more 

Reinforcement Learning-Based Focality Optimization for Multi-Electrode Temporal Interference Stimulation.

IEEE transactions on bio-medical engineering Jun 1, 2026
OBJECTIVE: Multi-electrode Temporal Interference Stimulation (TIS) is a promising noninvasive technology for deep brain stimulation, but its clinical translation is hindered by the challenge of optimizing its high-dimensional and hybrid parameter spa... read more 

Cross-Hemispheric Spatial-Temporal Attention Network for Decoding Silent Speech From EEG.

IEEE transactions on bio-medical engineering Jun 1, 2026
OBJECTIVE: Speech, as the core of advanced human cognition, is fundamental to social interaction and daily life. Electroencephalogram (EEG)-based speech brain-computer interface (BCI) offers a novel communication pathway for patients with speech diso... read more 

Manifold Learning Approaches for Characterizing Photoplethysmographic Signals.

IEEE transactions on bio-medical engineering Jun 1, 2026
OBJECTIVE: Photoplethysmography (PPG) is widely used for cardiovascular monitoring, but its analysis is challenged by signal variability, inconsistent acquisition settings, and limited interpretability. This study investigates the use of low-dimensio... read more 

A Hierarchical Multimodal Framework for Sedation Monitoring in ICU Patients.

IEEE transactions on bio-medical engineering Jun 1, 2026
In the intensive care unit (ICU), monitoring sedation levels is crucial. Clinicians often rely on intermittent behavioral scales like the Richmond Agitation-Sedation Scale (RASS), which can be subjective and delay timely interventions. While electroe... read more 
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