We conducted an observational study with 150 undergraduate nursing students to verify the usefulness of problem-based learning in the classroom and to ascertain whether this methodology facilitated the development of their knowledge acquisition skills. Problem-based learning fostered the development of integrated knowledge acquisition skills among nursing students.
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http://dx.doi.org/10.1097/NNE.0000000000000202 | DOI Listing |
Brief Bioinform
November 2024
School of Science, China Pharmaceutical University, Nanjing 211198, China.
The supervision of novel psychoactive substances (NPSs) is a global problem, and the regulation of NPSs was heavily relied on identifying structural matches in established NPSs databases. However, violators could circumvent legal oversight by altering the side chain structure of recognized NPSs and the existing methods cannot overcome the inaccuracy and lag of supervision. In this study, we propose a scaffold and transformer-based NPS generation and Screening (STNGS) framework to systematically identify and evaluate potential NPSs.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
December 2024
Department of Respiration, Peking Union Medical College Hospital, No.1, Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
Background: Inpatients with high risk of venous thromboembolism (VTE) usually face serious threats to their health and economic conditions. Many studies using machine learning (ML) models to predict VTE risk overlook the impact of class-imbalance problem due to the low incidence rate of VTE, resulting in inferior and unstable model performance, which hinders their ability to replace the Padua model, a widely used linear weighted model in clinic. Our study aims to develop a new VTE risk assessment model suitable for Chinese medical inpatients.
View Article and Find Full Text PDFBMC Med Educ
December 2024
Department of Neurology, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, 100029, China.
Background: In China, investigations into the efficacy of neurological clinical teaching try to ascertain the impacts of various teaching methods on intervention outcomes. However, these studies often suffer from limited sample sizes, single-center studies and low quality, compounded by the lack of direct comparative analyses between teaching methods, thereby leaving the identification of the most effective method unresolved. This study aims to compare the effectiveness of various teaching methods in the standardized training of Chinese neurology clinicians to inform an optimal teaching model utilizing a Bayesian network meta-analysis (NMA) approach.
View Article and Find Full Text PDFAdv Med Educ Pract
December 2024
Graduate School of Education, Stanford University, Stanford, California, USA.
Background: Numerous challenges exist in effectively bridging theory and practice in the teaching and assessment of clinical reasoning, despite an abundance of theoretical models. This study compares clinical reasoning practices and decisions between medical students and expert clinicians using a problem-solving framework from the learning sciences, which identifies clinical reasoning as distinct, observable actions in clinical case solving. We examined students at various training stages against expert clinicians to address the research question: How do expert clinicians and medical students differ in their practices and decisions during the diagnostic process?.
View Article and Find Full Text PDFNetwork
December 2024
Department of Information Management, Asia Eastern University of Science and Technology, New Taipei, Panchiao, Taiwan.
To improve the calculation accuracy of the Monte Carlo (MC) method and reduce the calculation time. Firstly, CNN and LSTM deep learning networks are introduced for designing nonlinear dynamic systems simulating dam stress. Then, spatial feature mining and sequence information extraction of nonlinear data of dam stress are carried out respectively, and a combined prediction model of dam stress depth (DS-FEM-CNN-LSTM) is proposed.
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