Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64845, first published .
Clinical Laboratory Parameter–Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study

Clinical Laboratory Parameter–Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study

Clinical Laboratory Parameter–Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study

Byungeun Shon   1 , MS ;   Sook Jin Seong   2 , MD, PhD ;   Eun Jung Choi   3 , PhD ;   Mi-Ri Gwon   3 , PhD ;   Hae Won Lee   3 , MD, PhD ;   Jaechan Park   4 , MD, PhD ;   Ho-Young Chung   1 , MD, PhD ;   Sungmoon Jeong   1 , PhD ;   Young-Ran Yoon   3 , MD, PhD

1 Department of Medical Informatics, School of Medicine, Kyungpook National University, Daegu, Republic of Korea

2 Center for Convergence Medical Research, School of Medicine, Kyungpook National University, Daegu, Republic of Korea

3 Department of Molecular Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea

4 Department of Neurosurgery, School of Medicine, Kyungpook National University, Daegu, Republic of Korea

Corresponding Author:

  • Young-Ran Yoon, MD, PhD
  • Department of Molecular Medicine
  • School of Medicine, Kyungpook National University
  • 680 Gukchaebosang-ro, Jung-gu
  • Daegu 41944
  • Republic of Korea
  • Phone: 82 534204950
  • Email: yry@knu.ac.kr