Generating Outpatient Progress Notes: A Comparison of Individualized and Generalized Models.

Journal: Studies in health technology and informatics
Published Date:

Abstract

The increasing documentation workload in medical practice, particularly for clinical notes, has driven the development of AI-driven solutions. This study introduces an AI Doctor Assistant (DA) that generates drafts of outpatient progress notes. The DA focuses on two main tasks: generating the operation summary section and the clinical findings section of progress notes. Using datasets from four medical specialties, this study compares the performance of individually fine-tuned models for each professor with a general model trained on data from all professors. Experimental results comparing individual and general models revealed that the general model's performance varied depending on the task type. These findings underline the AI DA's potential to reduce documentation burdens and improve generalized ability across diverse clinical scenarios.

Authors

  • Jinsig Yoo
    Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University, South Korea.
  • Hyeryun Park
    Interdisciplinary Program for Bioengineering, Seoul National University Graduate School, Seoul, Republic of Korea.
  • Somin Song
    Medical Research Center, Institute of Medical and Biological Engineering, Seoul National University.
  • Jiyeon Dang
    Medical Research Center, Institute of Medical and Biological Engineering, Seoul National University.
  • Jinwook Choi
    Dept. of Biomedical Engineering, College of Medicine, Seoul National University 103, Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. Electronic address: jinchoi@snu.ac.kr.