BACKGROUND: Delirium frequently complicates elderly chronic kidney disease (CKD) patients due to multifactorial vulnerability. Early detection in geriatric intensive care unit (ICU) settings is challenged by traditional assessments' communication def...
BACKGROUND: This study explored the diagnostic accuracy of artificial intelligence (AI) chatbots and dental students when responding to questions related to pulpal and periapical diseases. Rapid advancements in AI have led to increased interest in th...
BACKGROUND: Numerous studies have manifested that cellular senescence involves in the pathogenesis of intervertebral disc degeneration (IDD). Here, we constructed a novel senescence-related genes (SRGs) signature for IDD.
BACKGROUND: More than 300 mutations in presenilin 1 (PSEN1) lead to autosomal dominant Alzheimer's disease (ADAD). PSEN1, as the catalytic subunit of γ-secretase, generates amyloid-β (Aβ) peptides through a sequential proteolysis of the amyloid precu...
The integration of Artificial Intelligence (AI) in medical education is rapidly transforming assessment practices, offering unprecedented opportunities to enhance student evaluation, feedback, and learning pathways. However, despite the potential, a ...
BACKGROUND: Accurate landmark localization is important for three-dimensional (3D) cephalometric analysis. Although deep learning has shown promising performance for 3D landmark localization, the high computational burden of processing volumetric dat...
BACKGROUND: Coronary computed tomography angiography (CCTA) is widely used as a first-line tool for diagnosing and managing coronary artery disease (CAD), and machine learning (ML)-based analysis shows promise for quantitative CAD assessment.
BACKGROUND: Accurate prediction of drug-target interactions (DTIs) is essential for advancing drug discovery. Although numerous computational methods have been proposed, many exhibit limited generalization, particularly when dealing with unseen drugs...
BMC medical informatics and decision making
Nov 26, 2025
Artificial intelligence (AI) has emerged as a promising tool to enhance medical practice and improve patient outcomes. However, introducing AI in interactions between patients, support persons (SPs) and physicians may create real or perceived informa...
BACKGROUND: Early identification of students at academic risk is critical in health sciences education, particularly in regions prioritizing healthcare workforce development. This study evaluated the application of established machine learning (ML) c...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.