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Deep learning prediction of mammographic breast density using screening data.
Scientific reports
Apr 4, 2025
This study investigated a series of deep learning (DL) models for the objective assessment of four categories of mammographic breast density (e.g., fatty, scattered, heterogeneously dense, and extremely dense). A retrospective analysis was conducted ...
Psychological Factors Influencing Appropriate Reliance on AI-enabled Clinical Decision Support Systems: Experimental Web-Based Study Among Dermatologists.
Journal of medical Internet research
Apr 4, 2025
BACKGROUND: Artificial intelligence (AI)-enabled decision support systems are critical tools in medical practice; however, their reliability is not absolute, necessitating human oversight for final decision-making. Human reliance on such systems can ...
Using a Hybrid of AI and Template-Based Method in Automatic Item Generation to Create Multiple-Choice Questions in Medical Education: Hybrid AIG.
JMIR formative research
Apr 4, 2025
BACKGROUND: Template-based automatic item generation (AIG) is more efficient than traditional item writing but it still heavily relies on expert effort in model development. While nontemplate-based AIG, leveraging artificial intelligence (AI), offers...
Greenspace and depression incidence in the US-based nationwide Nurses' Health Study II: A deep learning analysis of street-view imagery.
Environment international
Apr 4, 2025
BACKGROUND: Greenspace exposure is associated with lower depression risk. However, most studies have measured greenspace exposure using satellite-based vegetation indices, leading to potential exposure misclassification and limited policy relevance. ...
Leveraging Artificial Intelligence to Uncover Symptom Burden in Palliative Care: Analysis of Nonscheduled Visits Using a Phi-3 Small Language Model.
JCO global oncology
Apr 4, 2025
PURPOSE: This study aimed to differentiate nonscheduled visits (NSVs) in an outpatient palliative care setting that are driven by or accompanied by uncontrolled symptoms from those that are administrative or routine, such as prescription refills and ...
Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care.
JCO clinical cancer informatics
Apr 4, 2025
PURPOSE: The use of real-world data (RWD) in oncology is becoming increasingly important for clinical decision making and tailoring treatment. Despite the significant success of targeted therapy and immunotherapy in advanced melanoma, substantial var...
A semantic segmentation model for automatic precise identification of pituitary microadenomas with preoperative MRI.
Neuroradiology
Apr 4, 2025
PURPOSE: Magnetic resonance imaging (MRI) is an essential technique for diagnosing pituitary adenomas; however, it is also challenging for neurosurgeons to use it to precisely identify some types of microadenomas. A novel neural network model was dev...
Towards clinical implementation of automated segmentation of vestibular schwannomas: a reliability study comparing AI and human performance.
Neuroradiology
Apr 4, 2025
PURPOSE: To evaluate the clinimetric reliability of automated vestibular schwannoma (VS) segmentations by a comparison with human inter-observer variability on T1-weighted contrast-enhanced MRI scans.
Comparison of Initial Artificial Intelligence (AI) and Final Physician Recommendations in AI-Assisted Virtual Urgent Care Visits.
Annals of internal medicine
Apr 4, 2025
BACKGROUND: Whether artificial intelligence (AI) assistance is associated with quality of care is uncertain.
sEMG-Based Gesture Recognition via Multi-Feature Fusion Network.
IEEE journal of biomedical and health informatics
Apr 4, 2025
The sparse surface electromyography-based gesture recognition suffers from the problems of feature information not richness and poor generalization to small sample data. Therefore, a multi-feature fusion network (MFF-Net) model is proposed in this pa...
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