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Clinical Trial Summary

The primary objective of this study is to examine the role of machine learning and computer aided diagnostics in automatic polyp detection and to determine whether a combination of colonoscopy and an automatic polyp detection software is a feasible way to increase adenoma detection rate compared to standard colonoscopy.


Clinical Trial Description

n/a


Study Design


Related Conditions & MeSH terms


NCT number NCT03637712
Study type Interventional
Source NYU Langone Health
Contact
Status Completed
Phase N/A
Start date September 1, 2018
Completion date July 7, 2019

See also
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Completed NCT04640792 - A Study to Evaluate the Safety and Efficacy of the Use of ME-APDS During Colonoscopy N/A
Recruiting NCT04422548 - Does AI-assisted Colonoscopy Improve Adenoma Detection in Screening Colonoscopy? N/A
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Completed NCT03458390 - Use of a Colon Irrigation Device as a Preparation for a Colon Visualization Procedure N/A
Completed NCT02194959 - Peer Patient Navigation for Colon Cancer Screening N/A
Terminated NCT01782014 - Comparison of Adenoma Detection Rate Among Water, Carbon Dioxide and Air Methods of Minimal Sedation Colonoscopy Phase 3
Completed NCT01838408 - Evaluation of Proposed EZ2go Complete Bowel Cleansing System N/A
Completed NCT04838951 - Effect of Real-time Computer-aided System (ENDO-AID) on Adenoma Detection in Endoscopist-in-training N/A