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
230 participants
INTERVENTIONAL
2020-05-01
2020-10-01
Brief Summary
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Detailed Description
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It is essential to know whether deep learning algorithms can really help endoscopists during colonoscopies. Several studies have already addressed this issue with different approaches and results. However, one common drawback of these type of Machine vs Human retrospective studies is endoscopist bias. It is usually generated because of human natural competitive spirit against machine or human relaxation because of AI-reliance. This can have an effect in the overall results.
The investigators perfomed colonoscopies with the use of a commercially available AI system to detect colonic polyps and recorded them during clinical routine. Additionally from March 2019 - May 2019, 120 colonoscopy videos were performed and captured prospectively without the use of AI.
In this study, the investigators plan to retrospectively compare those two video sets regarding the polyp detection rate, withdrawal time and polyp identification characteristics of the AI system.
Conditions
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Study Design
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NON_RANDOMIZED
PARALLEL
DIAGNOSTIC
NONE
Study Groups
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Colonoscopy with AI-assistance group
Colonoscopies were performed with AI-assistance.
AI-assisted colonoscopy
Colonoscopies performed with assistance of an AI tool that highlights the areas that are susceptible to be a polyp.
Standard Colonoscopy group
Standard clinical procedure
No interventions assigned to this group
Interventions
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AI-assisted colonoscopy
Colonoscopies performed with assistance of an AI tool that highlights the areas that are susceptible to be a polyp.
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
* Colonoscopies for work up of an active bleeding
18 Years
ALL
No
Sponsors
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Wuerzburg University Hospital
OTHER
Responsible Party
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Alexander Hann
Principal Investigator
Principal Investigators
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Alexander Hann, PD Dr. Med
Role: PRINCIPAL_INVESTIGATOR
Wuerzburg University Hospital
Locations
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Universitätsklinikum Würzburg
Würzburg, Bavaria, Germany
Countries
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Other Identifiers
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AI01
Identifier Type: -
Identifier Source: org_study_id
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