Development and Validation of a Multi-Task Artificial Intelligence-Assisted System for Small Bowel Capsule Endoscopy.

Journal: International journal of general medicine
Published Date: Jan 1, 2025

Abstract

OBJECTIVE: To develop a multi-task artificial intelligence-assisted system for small bowel capsule endoscopy (SBCE) based on various Transformer neural network architectures. The system integrates lesion recognition, cumulative time statistics, and progress bar marking functions to enhance the efficiency and accuracy of endoscopic image interpretation while effectively reducing missed diagnoses.

Authors

  • Jian Chen
    School of Pharmacy, Shanghai Jiaotong University, Shanghai, China.
  • Hongwei Wang
    Department of Oncological Surgery, Harbin Medical University Cancer Hospital, Harbin, 150000, Heilongjiang Province, China.
  • Zihao Zhang
    Institute for Hospital Management, Tsinghua University, Beijing, China.
  • Kaijian Xia
    Intelligent Medical Technology Research Center, Changshu Hospital Affiliated to Soochow University, Changshu, China.
  • Fuli Gao
    Department of Gastroenterology, Changshu Hospital Affiliated to Soochow University, First People's Hospital of Changshu City, No.1 Shuyuan Street, Changshu, Jiangsu, 215500, China.
  • Xiaodan Xu
    Department of Gastroenterology, Changshu Hospital Affiliated to Soochow University, First People's Hospital of Changshu City, No.1 Shuyuan Street, Changshu, Jiangsu, 215500, China. xuxiaodan20@126.com.
  • Ganhong Wang
    Department of Gastroenterology, Changshu Traditional Chinese Medicine Hospital (New District Hospital), Suzhou, 215500, China.

Keywords

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