Will AI improve the quality of acquired images for endoscopic remission assessment of UC?

Prospective study of whether AI improves the quality of acquired images for endoscopic remission assessment of UC - UC-AI studyc

Status

Recruiting

Phases

Unknown

Study type

Interventional

Source

JPRN

Registry ID

JPRN-UMIN000047775

Enrollment

100

Registered

2022-05-16

Start date

2022-05-16

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

No use of AI system (EB-UC2) for endoscopic remission assessment of UC Use of the AI system (EB-UC2) for endoscopic remission assessment of UC

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: White light endoscopic images that were acquired from the following patients; Patients who underwent colonoscopy for clinical necessity at Showa University Northern Yokohama Hospital. Patients undergoing colonoscopy by a non-specialist. Patients who have given consent to participate in the study.

Exclusion criteria

Exclusion criteria: Images of neoplastic lesions. Images of the small intestinal mucosa

Design outcomes

Primary

Measure	Time frame
The difference in acquisition rate of evaluation-inappropriate images with and without the use of EB-UC2	—

Secondary

Measure	Time frame
The difference in diagnostic concordance rates of acquired images with and without the use of EB-UC2	—

Countries

Japan

Contacts

Public ContactYasuharu Maeda

Showa University Northern Yokohama Hospital Digestive Disease Center

yasuharumaeda610@hotmail.com0459497000

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Jul 3, 2026