Development and clinical validation of deep learning-based immunohistochemistry prediction models for subtyping and staging of gastrointestinal cancers.

Journal: BMC gastroenterology
Published Date:

Abstract

BACKGROUND: Immunohistochemistry (IHC) is a critical tool for tumor diagnosis and treatment, but it is time and tissue consuming, and highly dependent on skilled laboratory technicians. Recently, deep learning-based IHC biomarker prediction models have been widely developed, but few investigations have explored their clinical application effectiveness.

Authors

  • Junxiao Wang
    School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China. dz1427034@smail.nju.edu.cn.
  • Shiying Zhang
    Department of Pathology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Jia Li
    Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Zhongshan Tsuihang New District, Guangdong, 528400, PR China; School of Pharmacy, Zunyi Medical University, Zunyi, 563000, PR China; National Center for Drug Screening, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, PR China.
  • Mei Deng
    Department of Neurosurgery, Guizhou Provincial People's Hospital, Guiyang, China.
  • Zhi Zeng
    Department of Pathology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Zehua Dong
    Department of Internal Medicine, Renmin Hospital of Wuhan University, 99 Zhangzhidong Road, Wuhan, 430060, Hubei Province, China.
  • Fangfang Chen
    College of Information Science and Engineering, Xinjiang University, Urumqi, Xinjiang, China.
  • Wen Liu
    Department of Dermatology, Air Force General Hospital, PLA Beijing 100142, China.
  • Lianlian Wu
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Honggang Yu
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.

Keywords

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