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The study of the application of deep learning algorithms in quality control during colonoscopy procedures

The study of the application of deep learning algorithms in quality control during colonoscopy procedures

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600122882
Enrollment
Unknown
Registered
2026-04-20
Start date
2026-04-20
Completion date
Unknown
Last updated
2026-04-27

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

Conditions

Quality Control Indicators for Colonoscopy

Interventions

Positive example group:None
Negative example group:None

Sponsors

Ya'an People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: (1) patients undergoing colonoscopy in the endoscopy center, including routine withdrawal videos and secondary withdrawal videos of right hemicolon; (2) The patients were over 18 years old.

Exclusion criteria

Exclusion criteria: (1) Patients treated with colonoscopy alone for gastrointestinal bleeding and colonic lesions; (2) The withdrawal of the endoscope does not include from the ileocecal junction to the hepatic flexure; (3) Patients with absent anatomical landmarks such as the ileocecal junction, hepatic flexure, and anus due to surgery or other reasons; (4) Patients deemed unsuitable for inclusion by other researchers.

Design outcomes

Primary

MeasureTime frame
The accuracy of secondary withdrawal monitoring of the right colon;Cecal intubation identification accuracy;Effective withdrawal time;

Secondary

MeasureTime frame
Polyp detection rate;

Countries

China

Contacts

Public ContactChen Ou

Ya'an People's Hospital

1027580516@qq.com+86 158 9269 3680

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 1, 2026