Deep learning model using stool pictures for predicting endoscopic mucosal inflammation in patients with ulcerative colitis.

Jung Won LeeDongwon WooKyeong Ok KimEun Soo Kim Sung Kook Kim Hyun Seok Lee Ben Kang Yoo Jin Lee Jeongseok Kim Byeong Ik Jang Eun Young Kim Hyeong Ho JoYun Jin ChungHanjun RyuSoo-Kyung ParkDong-Il Park Hosang Yu Sungmoon Jeongnull null

Published in: The American journal of gastroenterology (2024)

DLSUC demonstrated a good discriminating power similar to that of Fcal in predicting endoscopic activity with improved accuracy in patients without rectal sparing. This study implies that stool photos are a useful monitoring tool for typical UC.

Keyphrases

ulcerative colitis
deep learning
end stage renal disease
newly diagnosed
ejection fraction
chronic kidney disease
peritoneal dialysis
prognostic factors
rectal cancer
artificial intelligence
convolutional neural network