Deep learning model for diagnosing gastric mucosal lesions using endoscopic images: development, validation, and method comparison
Joon Yeul Nam(Seoul National University), Jeong‐Hoon Lee(Ulsan College), Hyuk Lee(Yonsei University), Hosim Soh(Seoul National University), Jong Chul Ye(Korea Advanced Institute of Science and Technology), Hyung Jin Chung(Seoul National University), Tae Jun Kim(Samsung Medical Center), Eun Ae Kang(Yonsei University), Soo‐Jeong Cho(Seoul National University), Sang Gyun Kim(Seoul National University Hospital), Hyunsoo Chung(Seoul National University), Joo Sung Kim(National University College), Jong Pil Im(Seoul National University), Kyu Sung Choi(Seoul National University Hospital)
Cited by 43
Related Papers
Validation of Microsatellite Instability Detection Using a Comprehensive Plasma-Based Genotyping Panel
|Clinical Cancer Research|2019|237
Gastric per-oral endoscopic myotomy for refractory gastroparesis: results from the first multicenter study on endoscopic pyloromyotomy (with video)
|Gastrointestinal Endoscopy|2016|218
Anti-MAdCAM antibody (PF-00547659) for ulcerative colitis (TURANDOT): a phase 2, randomised, double-blind, placebo-controlled trial
|The Lancet|2017|198
Anti‐inflammatory mechanism of metformin and its effects in intestinal inflammation and colitis‐associated colon cancer
|Journal of Gastroenterology and Hepatology|2013|180
Mucosal Mast Cell Count Is Associated With Intestinal Permeability in Patients With Diarrhea Predominant Irritable Bowel Syndrome
|Journal of Neurogastroenterology and Motility|2013|117