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

Machine Learning (2115) Clinical Information and Decision Making (1950) Artificial Intelligence (2180) Decision Support for Health Professionals (1560) Precision Medicine (164)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72679, first published .
Automated Classification of Lymphoma Subtypes From Histopathological Images Using a U-Net Deep Learning Model: Comparative Evaluation Study

Automated Classification of Lymphoma Subtypes From Histopathological Images Using a U-Net Deep Learning Model: Comparative Evaluation Study

Automated Classification of Lymphoma Subtypes From Histopathological Images Using a U-Net Deep Learning Model: Comparative Evaluation Study

Authors of this article:

Jin Zhao1 Author Orcid Image ;   Xiaolian Wen1 Author Orcid Image ;   Li Ma1 Author Orcid Image ;   Liping Su1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Jin Zhao   1 * , MM ;   Xiaolian Wen   1 * , MM ;   Li Ma   1 , MD ;   Liping Su   1 , MD

1 Department of Hematology, Cancer Hospital Affiliated to Shanxi Medical University, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Taiyuan, China

*these authors contributed equally

Corresponding Author:

  • Liping Su, MD
  • Department of Hematology
  • Cancer Hospital Affiliated to Shanxi Medical University, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences
  • No. 3, Zhigong New Street
  • Taiyuan 030013
  • China
  • Phone: 86 0351-4650984
  • Email: sxsulp2005@163.com