Application of AI in Polypectomy

July 23, 2020 updated by: Yanqing Li

Application of Artificial Intelligence in Colorectal Polypectomy

The aim of this study was to assess the performance of AI system in polypectomy

Study Overview

Status

Unknown

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Anticipated)

1000

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • China
    • Shandong
      • Jinan, Shandong, China
        • Recruiting
        • Department of Gastroenterology, Qilu Hospital, Shandong University
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 80 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Inclusion Criteria:

  • to undergo colorectal polypectomy;
  • agree to give written informed consent

Exclusion Criteria:

  • patients with the contraindications to colorectal polypectomy;
  • patients with a history of inflammatory bowel disease (IBD), CRC, colorectal surgery;
  • patients with high suspicion of polyposis syndromes, IBD and typical advanced CRC;
  • patients refused to participate in the trial;
  • the procedure cannot be completed due to stenosis, obstruction, huge occupying lesions, or solid stool;
  • the procedure have to be terminated due to complications of anaesthesia.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Other
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Double

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
No Intervention: control group
Experimental: AI-aided group
Other: AI system
The real-time assistance of AI system

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
polypectomy time
Time Frame: 12 months
the time for detection in polypectomy
12 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Yanqing Li

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Anticipated)

July 21, 2020

Primary Completion (Anticipated)

July 21, 2021

Study Completion (Anticipated)

September 21, 2021

Study Registration Dates

First Submitted

July 14, 2020

First Submitted That Met QC Criteria

July 23, 2020

First Posted (Actual)

July 24, 2020

Study Record Updates

Last Update Posted (Actual)

July 24, 2020

Last Update Submitted That Met QC Criteria

July 23, 2020

Last Verified

July 1, 2020

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2020SDU-QILU-0714

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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