Artificial Intelligence for Determination of Gastroscopy Surveillance Intervals
NCT ID: NCT05631015
Last Updated: 2022-11-30
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
2000 participants
OBSERVATIONAL
2012-01-01
2023-12-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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OTHER
RETROSPECTIVE
Study Groups
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Artificial Intelligence support decision group
According the endoscopic reports and pathological reports, the decision support system recognise patients' disease types and grades, and generate guidelines based survilliance or treatment recommendations.
AI recongnize disease and generate recommendations
According the endoscopic reports and pathological reports, the decision support system recognise patients' disease types and grades, and generate guidelines based survilliance or treatment recommendations.
Interventions
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AI recongnize disease and generate recommendations
According the endoscopic reports and pathological reports, the decision support system recognise patients' disease types and grades, and generate guidelines based survilliance or treatment recommendations.
Eligibility Criteria
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Inclusion Criteria
* Patients underwent endoscopic examination
Exclusion Criteria
* Patients with imcomplete examination information
* Patients undergo endoscopy for therapy
* Patients have history of upper gastrointestinal surgery
* Patients with duodenal or Laryngeal neoplasms
* Patients with gastrointestinal submucosal tumor
18 Years
80 Years
ALL
No
Sponsors
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Xiuli Zuo
OTHER
Responsible Party
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Xiuli Zuo
director of Qilu Hospital gastroenterology department
Locations
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Qilu Hospital, Shandong University
Jinan, Shandong, China
Countries
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Other Identifiers
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2022-SDU-QILU-G008
Identifier Type: -
Identifier Source: org_study_id