Knowledge-point classification using simple LSTM-based and siamese-based networks for virtual patient simulation.

Journal: BMC medical informatics and decision making
PMID: 39856663

Abstract

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. This study aimed to extract insights from case summaries and patient interviews to improve evaluation and feedback in medical education.

Authors

  • Yih-Lon Lin
    Department of Information Engineering, I-Shou University, Kaohsiung, Taiwan.
  • Yu-Min Chiang
    Department of Automation Engineering, National Formosa University, No.64, Wunhua Rd., 632 Huwei Township, Yunlin, Taiwan. ymchiang@nfu.edu.tw.
  • Tsuen-Chiuan Tsai
    Landseed International Hospital, Taoyuan City, Taiwan.
  • Sheng-Gui Su
    Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Yunlin, Taiwan.

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