Evaluation of ulcerative colitis with deep neural networks based on endoscopic images
Not Applicable
- Conditions
- lcerative colitis
- Registration Number
- JPRN-UMIN000031430
- Lead Sponsor
- Department of Endoscopy, Tokyo Medical and Dental University
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Complete: follow-up complete
- Sex
- All
- Target Recruitment
- 500
Inclusion Criteria
Not provided
Exclusion Criteria
i) patients with prior colon surgery, IBD unclassified, Crohns disease, colorectal neoplasia, or concomitant infectious colitis ii) patients for whom colonoscopy were contraindicated iii) patients for whom biopsy were contraindicated because of blood disease or antithrombotic or anticoagulation therapy.
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method accuracy of DNN-UC to evaluate endoscopic and histological healing
- Secondary Outcome Measures
Name Time Method i) ability of DNN-UC to score UCEIS ii) accuracy of DNN-UC for endoscopic and histological healing in each segment iii) accuracy of DNN-UC in each confidence case iv) accuracy of DNN-UC stratified with the degree of colon cleaning.