There is a currently an unmet need for non-invasive methods to predict the risk of esophageal squamous cell carcinoma (ESCC). Previously, we found that specific soft palate morphologies are strongly associated with increased ESCC risk. However, there...
Integrative psychological & behavioral science
Feb 1, 2025
This study draws on the cultural-historical perspectives of Vygotsky and Galperin to examine the role of AI-generated feedback within the Assessment for Learning (AfL) process in fostering students' development as learners. By leveraging Galperin's c...
The bidirectional interactions between brain and heart through autonomic nervous system is the prime focus of neuro-cardiology community. The computer models designed to analyze brain and heart signals are either complex in terms of molecular and cel...
PURPOSE OF REVIEW: This review discusses the transformative potential of artificial intelligence (AI) in ischemic heart disease (IHD) prevention. It explores advancements of AI in predictive modeling, biomarker discovery, and cardiovascular imaging. ...
PURPOSE: Despite increased awareness of sleep hygiene, over 80% of sleep apnea cases remain undiagnosed, underscoring the need for accessible screening methods. This study presents a method for detecting sleep apnea using data from the Apple Watch's ...
Cancer immunology, immunotherapy : CII
Feb 1, 2025
With the incorporation of immune checkpoint inhibitors into the treatment of endometrial cancer (EC), a deeper understanding of the tumor immune microenvironment is critical. Tertiary lymphoid structures (TLSs) are considered favorable prognostic fac...
Journal of neuroengineering and rehabilitation
Feb 1, 2025
OBJECTIVE: This study aimed to develop and validate a machine learning-based predictive model for gait recovery in patients with acute anterior circulation ischemic stroke.
BACKGROUND: The traditional process of developing new drugs is time-consuming and often unsuccessful, making drug repurposing an appealing alternative due to its speed and safety. Graph neural networks (GCNs) have emerged as a leading approach for pr...
Vision-language artificial intelligence models (VLMs) possess medical knowledge and can be employed in healthcare in numerous ways, including as image interpreters, virtual scribes, and general decision support systems. However, here, we demonstrate ...
AIMS: The aim of this study was to develop and evaluate a deep learning-based model for classification of hip fractures to enhance diagnostic accuracy.
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