Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Sep 1, 2025
PURPOSE: Unlike established knee phenotype classifications, the recently introduced Citak classifications describe the intrafemoral and intratibial knee morphology. The aim of this study was to evaluate the distribution of Citak types A, B and C of t...
Journal of magnetic resonance imaging : JMRI
Sep 1, 2025
BACKGROUND: Deep learning (DL) models for accurate renal tumor characterization may benefit from multi-center datasets for improved generalizability; however, data-sharing constraints necessitate privacy-preserving solutions like federated learning (...
This study aimed to classify patients' focal (frontal, temporal, parietal, occipital), multifocal, and generalized epileptiform activities based on EEG findings using artificial intelligence models. The study included 575 patients followed in the Neu...
BACKGROUND: Nursing students' acceptance and usage of AI are crucial for embracing and implementing the technology in nursing practice in the future. However, there is a lack of literature to examine the factors affecting AI usage intention among nur...
PURPOSE: To evaluate the accuracy of 11 intraocular lens (IOL) calculation formulas in eyes undergoing Descemet membrane endothelial keratoplasty (DMEK) combined with cataract surgery (triple DMEK).
RATIONALE AND OBJECTIVES: Radiogenomics holds promise in identifying molecular alterations in nonsmall cell lung cancer (NSCLC) using imaging features. Previously, we developed a radiogenomics model to predict epidermal growth factor receptor (EGFR) ...
Autism spectrum disorder (ASD) is characterized by deficits in social communication and repetitive behaviors/restricted interests that may be diagnosed as early as 2 years of age. This suggests that the pathology underlying the disorder is present du...
Academic medicine : journal of the Association of American Medical Colleges
Sep 1, 2025
PROBLEM: Despite the rapidly expanding role of artificial intelligence (AI) and machine learning (ML) in health care, a significant knowledge gap remains among clinicians in their ability to evaluate and use AI and ML tools.
PURPOSE: To investigate the usefulness of a machine learning (ML) model that can predict the natural course of childhood myopia in evaluation of the inhibitory effects of 0.125% atropine on the progression of childhood myopia.
BackgroundPatient safety is a critical component of health care systems. Large groups of patients, as a result of medical errors, are at risk of harm. OBJECTIVE: This study evaluated the patient safety culture (PSC) between different work groups in b...
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