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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UNKNOWN
40 participants
OBSERVATIONAL
2020-01-01
2020-05-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Artificial Intelligence
Artificial Intelligence System for Detection of colorectal polyps
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
Interventions
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Artificial Intelligence System for Detection of colorectal polyps
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
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
* uncontrolled coagulopathy
* known polyps or referral for polypectomy
18 Years
85 Years
ALL
Yes
Sponsors
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University of Erlangen-Nürnberg Medical School
OTHER
Responsible Party
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Timo Rath
Professor of Endoscopy
Locations
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University Hospital Erlangen
Erlangen, , Germany
Countries
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Central Contacts
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Facility Contacts
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References
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Pfeifer L, Neufert C, Leppkes M, Waldner MJ, Hafner M, Beyer A, Hoffman A, Siersema PD, Neurath MF, Rath T. Computer-aided detection of colorectal polyps using a newly generated deep convolutional neural network: from development to first clinical experience. Eur J Gastroenterol Hepatol. 2021 Dec 1;33(1S Suppl 1):e662-e669. doi: 10.1097/MEG.0000000000002209.
Other Identifiers
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CAID
Identifier Type: -
Identifier Source: org_study_id
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