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Knowledge-point classification using simple LSTM-based and siamese-based networks for virtual patient simulation.
BMC Med Inform Decis Mak
January 2025
Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Yunlin, Taiwan.
Background: In medical education, enhancing thinking skills is vital. The Virtual Diagnosis and Treatment Platform (VP) refines medical students' diagnostic abilities through interactive patient interviews (simulated patient interactions). By analyzing the questions asked during these interviews, the VP evaluates students' aptitude in medical history inquiries, offering insights into their thinking capabilities.
View Article and Find Full Text PDFEpitome of the Region-Regional Nostalgia Design Based on Digital Twins.
Behav Sci (Basel)
December 2024
Smart Design Lab, School of Design, Northumbria University, Newcastle upon Tyne NE1 8ST, UK.
Nostalgic scenes can trigger nostalgia to a considerable extent and can be effectively used as a nostalgic trigger that contributes to the psychological comfort of the elderly and immigrant populations, but a design system has not been adequately studied. Therefore, the design principles and digital twin (DT) design system of nostalgic scenes is proposed in this study. It focuses on the construction of a nostalgic scene DT model based on the system of system (SoS) theory.
View Article and Find Full Text PDFUsing the mind map method in medical education, its advantages and challenges: A systematic review.
J Educ Health Promot
December 2024
Department of Operating Room, Master of Science in Operating Room, Iran University of Medical Sciences, Tehran, Iran.
Mind mapping stands as a contemporary approach to education, introducing an innovative means of teaching and learning. In current times, this technique is embraced due to its ability to enhance the learning and retention process. This investigation explored the imperative nature of adopting novel educational methodologies such as mind mapping, while also examining its benefits and constraints.
View Article and Find Full Text PDFExploration of transfer learning techniques for the prediction of PM.
Sci Rep
January 2025
Institute for Anthropological Research, 10000, Zagreb, Croatia.
Modelling of pollutants provides valuable insights into air quality dynamics, aiding exposure assessment where direct measurements are not viable. Machine learning (ML) models can be employed to explore such dynamics, including the prediction of air pollution concentrations, yet demanding extensive training data. To address this, techniques like transfer learning (TL) leverage knowledge from a model trained on a rich dataset to enhance one trained on a sparse dataset, provided there are similarities in data distribution.
View Article and Find Full Text PDFExplaining cognitive function in multiple sclerosis through networks of grey and white matter features: a joint independent component analysis.
J Neurol
January 2025
NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, Faculty of Brain Sciences, UCL Queen Square Institute of Neurology, University College London, Queen Square, London, WC1N 3BG, UK.
Cognitive impairment (CI) in multiple sclerosis (MS) is only partially explained by whole-brain volume measures, but independent component analysis (ICA) can extract regional patterns of damage in grey matter (GM) or white matter (WM) that have proven more closely associated with CI. Pathology in GM and WM occurs in parallel, and so patterns can span both. This study assessed whether joint-ICA of GM and WM features better explained cognitive function compared to single-tissue ICA.
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