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

Machine Learning (2164) Pathology and Laboratory Medicine (33) AI applications in genomics and pathology informatics, including ‘Generative AI’ (24) Artificial Intelligence (2242) Applications of AI (315)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/84417, first published .
Ranking-Aware Multiple Instance Learning for Histopathology Slide Classification: Development and Validation Study

Ranking-Aware Multiple Instance Learning for Histopathology Slide Classification: Development and Validation Study

Ranking-Aware Multiple Instance Learning for Histopathology Slide Classification: Development and Validation Study

Authors of this article:

Ho Heon Kim1, 2 Author Orcid Image ;   Gisu Hwang1 Author Orcid Image ;   Won Chan Jeong1 Author Orcid Image ;   Young Sin Ko1, 3 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Ho Heon Kim   1, 2 * , MS ;   Gisu Hwang   1 * , MS ;   Won Chan Jeong   1 , BS ;   Young Sin Ko   1, 3 , MD, PhD

1 AI R&D Center, Seegene Medical Foundation, Seoul, Republic of Korea

2 Department of Medical Sciences, Graduate School, The Catholic University of Korea, Seoul, Republic of Korea

3 Pathology Center, Seegene Medical Foundation, Seoul, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Young Sin Ko, MD, PhD
  • AI R&D Center, Seegene Medical Foundation
  • 17F, Seegene Medical Tower, 288 Dapsimni-ro, Dongdaemun-gu
  • Seoul 02637
  • Republic of Korea
  • Phone: 82 2-2228-9349
  • Email: noteasy@mf.seegene.com