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This paper is in the following e-collection/theme issue:

Ontologies, Classifications, and Coding (472) Electronic Health Records (1796) Artificial Intelligence (5033) AI for Synthetic Data (28)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/91313, first published .
Doctor in white coat using tablet in modern office, discussing telemedicine

Synthetic Medical Document Generation Pipeline (MedDocSynth) for Optical Character Recognition: Development and Validation Study on Korean Clinical Documents

Synthetic Medical Document Generation Pipeline (MedDocSynth) for Optical Character Recognition: Development and Validation Study on Korean Clinical Documents

Authors of this article:

Mikel Lainsa1 Author Orcid Image ;   Javier Aguirre1 Author Orcid Image ;   Moon Hyeyoon1 Author Orcid Image ;   Won Yejun1 Author Orcid Image ;   Woojin Jang1 Author Orcid Image ;   Jong Eun Park2 Author Orcid Image ;   Won Chul Cha3 Author Orcid Image
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Mikel Lainsa   1 , MS ;   Javier Aguirre   1 , MS ;   Moon Hyeyoon   1 , BS ;   Won Yejun   1 , BS ;   Woojin Jang   1 , BS ;   Jong Eun Park   2 * , MD ;   Won Chul Cha   3 * , MD, PhD

1 Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea

2 Samsung Medical Center, Seoul, Republic of Korea

3 Department of Emergency Medicine, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Won Chul Cha, MD, PhD
  • Department of Emergency Medicine
  • Sungkyunkwan University School of Medicine, Samsung Medical Center
  • 81 Irwon-ro, Gangnam-gu
  • Seoul 06351
  • Republic of Korea
  • Phone: 82 2-3410-2053
  • Email: docchaster@gmail.com