Efficacy of Artificial Intelligence-assisted Colonic Polyp Detection System
NCT ID: NCT05941689
Last Updated: 2023-10-10
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
1906 participants
INTERVENTIONAL
2023-07-25
2023-09-30
Brief Summary
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
DIAGNOSTIC
DOUBLE
Study Groups
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AI-assisted group
Subjects in this group undergo AI-assisted colonoscopy. The AI-assisted system not only has the function of automatic polyp detection, but also has the function of colonoscopy quality control.
AI-assisted colonoscopy
AI can not only detect suspicious lesions timely, and label them in the field of view of the colonoscopy, but also monitor withdrawal speed and calculate the clean withdrawal time automatically.
control group
Subjects in this group undergo routine colonoscopy.
No interventions assigned to this group
Interventions
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AI-assisted colonoscopy
AI can not only detect suspicious lesions timely, and label them in the field of view of the colonoscopy, but also monitor withdrawal speed and calculate the clean withdrawal time automatically.
Eligibility Criteria
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Exclusion Criteria
18 Years
85 Years
ALL
Yes
Sponsors
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Xiangya Hospital of Central South University
OTHER
Responsible Party
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Principal Investigators
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Xiaowei Liu, doctor
Role: PRINCIPAL_INVESTIGATOR
Xiangya Hospital of Central South University
Locations
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Xiangya Hospital Central South University
Changsha, Hunan, China
Loudi Central Hospital
Loudi, Hunan, China
Countries
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Other Identifiers
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202306499
Identifier Type: -
Identifier Source: org_study_id
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