Accurate diagnosis of endoscopic mucosal healing in ulcerative colitis using deep learning and machine learning.

Journal: Journal of the Chinese Medical Association : JCMA
PMID: 34050105

Abstract

BACKGROUND: In clinical applications, mucosal healing is a therapeutic goal in patients with ulcerative colitis (UC). Endoscopic remission is associated with lower rates of colectomy, relapse, hospitalization, and colorectal cancer. Differentiation of mucosal inflammatory status depends on the experience and subjective judgments of clinical physicians. We developed a computer-aided diagnostic system using deep learning and machine learning (DLML-CAD) to accurately diagnose mucosal healing in UC patients.

Authors

  • Tien-Yu Huang
    Division of Gastroenterology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.
  • Shan-Quan Zhan
    Institute of Data Science and Engineering, National Chiao Tung University, Taiwan.
  • Peng-Jen Chen
    Division of Gastroenterology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
  • Chih-Wei Yang
    Department of Nephrology, Chang Gung Memorial Hospital at Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan; Kidney Research Center, Chang Gung Memorial Hospital at Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan.
  • Henry Horng-Shing Lu
    Shing-Tung Yau Center, National Chiao Tung University, 1001 University Road, Hsinchu City, Taiwan. hslu@stat.nctu.edu.tw.

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