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

Artificial Intelligence (1626) Clinical Information and Decision Making (1571) Digital Health Reviews (1452) Digital Biomarkers and Digital Phenotyping (218) Machine Learning (1649) Decision Support for Health Professionals (1302) Computer-Aided Diagnosis (168) mHealth for Diagnosis (67) Quality/Credibility of eHealth Information and Trust Issues (584) Cancer Prognosis Models and Machine Learning (20) Pathology and Laboratory Medicine (17)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/62851, first published .
Artificial Intelligence in Lymphoma Histopathology: Systematic Review

Artificial Intelligence in Lymphoma Histopathology: Systematic Review

Artificial Intelligence in Lymphoma Histopathology: Systematic Review

Authors of this article:

Yao Fu1 Author Orcid Image ;   Zongyao Huang2 Author Orcid Image ;   Xudong Deng3 Author Orcid Image ;   Linna Xu2 Author Orcid Image ;   Yang Liu2 Author Orcid Image ;   Mingxing Zhang2 Author Orcid Image ;   Jinyi Liu4 Author Orcid Image ;   Bin Huang2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Yao Fu   1 , MMedSc ;   Zongyao Huang   2 , MD ;   Xudong Deng   3 , BSc ;   Linna Xu   2 , MMedSc ;   Yang Liu   2 , MD ;   Mingxing Zhang   2 , BMed ;   Jinyi Liu   4 , BMed ;   Bin Huang   2 , MMedSc

1 Sichuan Tianfu New Area People's Hospital, Chengdu, China

2 Department of Pathology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China

3 Wonders Information Co., Ltd, Shanghai, China

4 Phase I Clinical Trial Unit, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, China

Corresponding Author:

  • Bin Huang, MMedSc
  • Department of Pathology
  • Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute
  • Sichuan Cancer Center, University of Electronic Science and Technology of China
  • South Renmin Road
  • Chengdu, 610041
  • China
  • Phone: 86 18236170185
  • Email: 18236170185@163.com