Post-contrast 3D T1-weighted MRI is a time consuming component of cancer neuroimaing protocols. The goal of this study is to accelerate the acquisition of 3D MRI using deep learning reconstruction of undersampled k-space data beyond clinically-availa... read more
Applied psychology. Health and well-being
Apr 1, 2026
Previous research has shown that advice sources influence individuals' risk perceptions and health decision-making. We conducted two experiments to examine differences in health risk assessment between AI algorithms and human peer groups, and how the... read more
This study compares two advanced deep learning models, nnU-Net and MA-SAM, for automatic segmentation of the left ventricle (LV) myocardium using 3D whole-heart T1 and T2 mapping, with the goal of evaluating their performance in terms of segmentation... read more
Therapeutic drug monitoring is essential for ensuring the efficacy and safety of vancomycin therapy in critically ill patients. This study aimed to develop a machine learning model for individualized prediction of vancomycin concentration-time curves... read more
Magnetic resonance elastography (MRE) enables non-invasive quantification of liver stiffness and plays a pivotal role in the assessment of hepatic fibrosis. However, clinical implementation remains limited by the need for manual delineation of region... read more
OBJECTIVES: This study aimed to develop and validate integrated prediction models for pediatric lupus nephritis (LN) treated with a mycophenolate mofetil (MMF)-based induction regimen (combined with glucocorticoids and hydroxychloroquine), incorporat... read more
An announcement was made in February 2026 that the Journal of Allied Health (JAH), the official scholarly publication of the Association of Schools Advancing Health Professions (ASAHP), seeks a new Editor-in-Chief. The change is one of many significa... read more
Small group work, defined as two or more students interdependently working together to achieve specific objectives, is a strategy that has been adopted in physical therapy and health professions curricula to foster deep learning and help develop clin... read more
International journal of neural systems
Apr 1, 2026
Interictal epileptiform discharges (IEDs) are crucial for epilepsy diagnosis but are often undetectable on scalp EEG (scEEG). This study aims to develop a Support Vector Machine classifier to detect mesial temporal lobe (MTL) IEDs invisible on scEEG ... read more
Sepsis, a life-threatening condition triggered by dysregulated host response to infection, poses significant global health challenges. Identifying lipopolysaccharide (LPS)-related biomarkers and underlying mechanisms remains critical, yet underexplor... read more
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.