Enhancing gastroenterology with multimodal learning: the role of large language model chatbots in digestive endoscopy.

Journal: Frontiers in medicine
Published Date: May 21, 2025

Abstract

INTRODUCTION: Advancements in artificial intelligence (AI) and large language models (LLMs) have the potential to revolutionize digestive endoscopy by enhancing diagnostic accuracy, improving procedural efficiency, and supporting clinical decision-making. Traditional AI-assisted endoscopic systems often rely on single-modal image analysis, which lacks contextual understanding and adaptability to complex gastrointestinal (GI) conditions. Moreover, existing methods struggle with domain shifts, data heterogeneity, and interpretability, limiting their clinical applicability.

Authors

  • Yuanyuan Qin
    Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Avenue, Wuhan, 430030, People's Republic of China. qinyuanyuan-1021@163.com.
  • Jianming Chang
    School of Computer Science and Engineering, Southeast University, Nanjing, China.
  • Li Li
    Department of Gastric Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
  • Mianhua Wu
    First Clinical Medical College, Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Cancer, Nanjing University of Chinese Medicine, Nanjing, China.

Keywords

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