Computer-aided Detection of Colorectal Polyps
Development and Validation of a New Artificial Intelligence System for Automated Detection of Colorectal Polyps During Colonoscopy
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Timo Rath, MD
- Phone Number: 45041 49 9131 85
- Email: timo.rath@uk-erlangen.de
Study Locations
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Erlangen, Germany, 91054
- Recruiting
- University Hospital Erlangen
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Contact:
- Timo Rath, Professor of Endoscopy
- Phone Number: 85 45041 49 9131
- Email: timo.rath@uk-erlangen.de
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- Screening or surveillance colonoscopy
Exclusion Criteria:
- known or suspected inflammatory bowel disease
- uncontrolled coagulopathy
- known polyps or referral for polypectomy
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Artificial Intelligence
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In this group, an artificial Intelligence System will be used for computer-aided diagnosis of colorectal polyps.
Diagnostic Performance of the artificial intelligence System for detection of polyps will be compared against Operator-based detection in the same group
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Feasibility to use the AI System in vivo during colonoscopy
Time Frame: 4 month
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As a Primary outcome, whether the AI System is capable of detecting colorectal polyps in vivo during colonoscopy
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4 month
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Diagnostic Performance of the AI System for detecting colorectal polyps
Time Frame: 4 month
|
As a secondary outcome, we assess the diagnostic Performance of the AI System for detecing colorectal Polyp in real time
|
4 month
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Collaborators and Investigators
Sponsor
Sponsor
Publications and helpful links
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Anticipated)
Primary Completion
Study Completion (Anticipated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- CAID
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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