Evaluation of ulcerative colitis with deep neural networks based on endoscopic images

Evaluation of ulcerative colitis with deep neural networks based on endoscopic images - DNN-UC

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000031430

Enrollment

500

Registered

2018-03-15

Start date

2018-04-01

Completion date

Unknown

Last updated

2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Ulcerative colitis

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: the patients who underwent colonoscopy for evaluation of UC

Exclusion criteria

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.

Design outcomes

Primary

Measure	Time frame
accuracy of DNN-UC to evaluate endoscopic and histological healing	—

Secondary

Measure	Time frame
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.	—

Countries

Japan

Contacts

Public ContactKento Takenaka

Tokyo Medical and Dental University Department of Endoscopy

ktakenaka.gast@tmd.ac.jp03-5803-5877

Outcome results