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REVIEW article

Front. Oncol.
Sec. Gastrointestinal Cancers: Gastric and Esophageal Cancers
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1437252

Applications of Artificial Intelligence in Digital pathology for Gastric Cancer

Provisionally accepted
Sheng Chen Sheng Chen 1Ping A. Ding Ping A. Ding 2*Hong h. Guo Hong h. Guo 2*Lingjiao Meng Lingjiao Meng 2*Qun Zhao Qun Zhao 2*
  • 1 Affiliated Hospital of Hebei University, Baoding, Hebei Province, China
  • 2 Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China

The final, formatted version of the article will be published soon.

    Gastric cancer is one of the most common cancers and is one of the leading causes of cancer-related deaths in worldwide. Early diagnosis and treatment are essential for a positive outcome. The integration of artificial intelligence in the pathology field is increasingly widespread, including histopathological images analysis. In recent years, the application of digital pathology technology emerged as a potential solution to enhance the understanding and management of gastric cancer. Through sophisticated image analysis algorithms, artificial intelligence technologies facilitate the accuracy and sensitivity of gastric cancer diagnosis and treatment and personalized therapeutic strategies. This review aims to evaluate the current landscape and future potential of artificial intelligence in transforming gastric cancer pathology, so as to provide ideas for future research.

    Keywords: gastric cancer, machine learning, digital pathology, artificial intelligence, Computational Pathology

    Received: 23 May 2024; Accepted: 07 Oct 2024.

    Copyright: © 2024 Chen, Ding, Guo, Meng and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Ping A. Ding, Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
    Hong h. Guo, Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
    Lingjiao Meng, Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
    Qun Zhao, Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.