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Development and Validation of an Artificial Intelligence-assisted Strategy Selection System for Colonoscopy Cleaning

NCT04444908 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 657

Last updated 2020-11-17

No results posted yet for this study

Summary

Patients with poor inadequate bowel preparation need to undergo secondary colonoscopy. but the evaluation of intestinal cleanliness is judged by doctors subjectively. there are no objective and effective criteria to guide the evaluation. We use the deep learning technique to develop the EndoAngel with real-time intestinal cleanliness assessment. It can derive a decision curve for bowel cleanliness based on the relationship between the percentage of bowel segments with a Boston score of 1 and the adenoma detection rate. It can help doctors to identify patients who need a second colonoscopy, and provide a new way for artificial intelligence in improving the detection rate of colonoscopic adenomas.

Conditions

  • Colorectal Adenoma

Sponsors & Collaborators

  • Renmin Hospital of Wuhan University

    lead OTHER

Principal Investigators

  • Honggang Yu, Doctor · Renmin Hospital of Wuhan University

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-05-11
Primary Completion
2020-10-15
Completion
2020-11-16

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04444908 on ClinicalTrials.gov