Open AccessAccurate diagnosis of endoscopic mucosal healing in ulcerative colitis using deep learning and machine learning
Author(s) -
Tsai-Wang Huang,
Shan Quan Zhan,
PengJen Chen,
Chih Wei Yang,
Henry Horng Shing Lu
Publication year - 2021
Publication title -
journal of the chinese medical association
Language(s) - English
Resource type - Journals
eISSN - 1728-7731
pISSN - 1726-4901
DOI - 10.1097/jcma.0000000000000559
Subject(s) - medicine , artificial intelligence , ulcerative colitis , grading (engineering) , gastroenterology , colectomy , endoscopic mucosal resection , endoscopy , computer science , disease , civil engineering , engineering
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.