Interpretable deep learning for gastric cancer detection: a fusion of AI architectures and explainability analysis.

Journal: Frontiers in immunology
Published Date: May 29, 2025

Abstract

INTRODUCTION: The rise in cases of Gastric Cancer has increased in recent times and demands accurate and timely detection to improve patients' well-being. The traditional cancer detection techniques face issues of explainability and precision posing requirement of interpretable AI based Gastric Cancer detection system.

Authors

  • Junjie Ma
    College of Education and Sports Sciences, Yangtze University, Jingzhou, China.
  • Fang Yang
    College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, People's Republic of China.
  • Rong Yang
    Robert F. Smith School of Chemical & Biomolecular Engineering, Cornell University, Ithaca, NY 14850, USA.
  • Yuan Li
    NHC Key Lab of Hormones and Development and Tianjin Key Lab of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Institute of Endocrinology, Tianjin, China.
  • Yongjing Chen
    Department of Gastroenterology, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, Shanxi, China.

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