A systematic review and meta-analysis found that virtual reality training significantly improved objectively assessed learning outcomes across health professions education, ...
A deep learning algorithm analyzing structural brain magnetic resonance imaging scans has accurately identified Alzheimer's disease pathology and predicted clinical ...
Researchers have developed PhysioSensAI, a deep learning framework that tracks real-time pain and evaluates movement quality during squat-based rehabilitation exercises.
A hybrid reinforcement learning framework combining Double Deep Q-Networks with Teaching-Learning-Based Optimization achieved 93.8 percent accuracy in planning adaptive mathematics ...
A new deep learning framework called CLAHE-RATSNet improves lung nodule segmentation in CT images by combining image enhancement with a ...
Researchers demonstrated that the FedDefend++ framework reinforces federated learning against model inversion and data poisoning attacks through trust-weighted aggregation, while ...
An offline deep learning system identified cattle muzzles with high benchmark accuracy but faced substantial accuracy drops and computational delays ...
An iterative deep learning framework accurately forecasts community disease surges three days ahead by analyzing coronavirus genetic material in municipal ...
A retrospective study shows that contrast-enhanced CT deep learning and habitat radiomics models effectively differentiate common pathological subtypes of small ...
A constructivist qualitative study of an eight-month program at Radboud university medical center found that longitudinal encounters between early medical ...
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