Artificial Intelligence Medical Compendium

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

Showing 6,821 to 6,830 of 205,891 articles

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

IEEE transactions on bio-medical engineering
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
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
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
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
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
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 

Prostate Targeting: Compact Robot With Harmonic Stepper Motors for MRI-Guided Needle Therapy.

IEEE transactions on bio-medical engineering
The superior image quality and excellent contrast offered by Magnetic Resonance Imaging (MRI) make it an ideal tool for guiding interventional procedures, particularly in targeting tumors within soft tissues. This paper presents an innovative robotic... read more 

Freezing depth prediction of surrounding rock in seasonally frozen tunnels based on bayes-optimized XGBoost.

Scientific reports
During freeze-thaw cycles, frost heave forces induced by pore water phase transition in the surrounding rock of seasonally frozen tunnels act continuously on the lining structure, impairing its stability and service performance. The evolution of free... read more 

Morpho-functional plasticity of tumour-associated macrophages: linking cell shape, ultrastructure, and immune regulation in cancer.

Clinical and experimental medicine
Macrophages are highly adaptable immune cells that play dual roles in the tumor microenvironment (TME), either promoting or restraining tumor progression. Their polarization into M1 and M2 tumor-associated macrophage (TAM) phenotypes is classically d... read more 

Machine learning for prediction and experimental validation of hydrochar characteristics via co-hydrothermal carbonization of sewage sludge and pomelo peel.

Bioresource technology
Optimizing the co-hydrothermal carbonization (co-HTC) of sludge and biomass requires understanding complex nonlinear relationships among feedstock characteristics, process parameters, and hydrochar properties. This study constructs an integrated mach... read more