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Clinical Trials/NCT04222439
NCT04222439
Unknown
Not Applicable

Development and Validation of a Deep Learning Algorithm for the Diagnosis of Gastrointestinal Diseases

Shandong University1 site in 1 country100,000 target enrollmentJanuary 1, 2020

Overview

Phase
Not Applicable
Intervention
Not specified
Conditions
Gastrointestinal Disease
Sponsor
Shandong University
Enrollment
100000
Locations
1
Primary Endpoint
The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm.
Last Updated
6 years ago

Overview

Brief Summary

The purpose of this study is to develop and validate a deep learning algorithm for the diagnosis of gastrointestinal diseases. Then, evaluate the accuracy this new artificial intelligence(AI) assisted recognition system in clinic practice.

Detailed Description

Recently, deep learning algorithm based on central neural networks (CNN) has shown multiple potential in computer-aided detection and computer-aided diagnose of gastrointestinal lesions. However, there is still a blank in recognition of all gastrointestinal diseases. This study aim to develop and validate a deep learning algorithm for the diagnosis of gastrointestinal diseases. Then, evaluate the accuracy this new artificial intelligence(AI) assisted recognition system in clinic practice.

Registry
clinicaltrials.gov
Start Date
January 1, 2020
End Date
February 2020
Last Updated
6 years ago
Study Type
Interventional
Study Design
Single Group
Sex
All

Investigators

Sponsor
Shandong University
Responsible Party
Principal Investigator
Principal Investigator

Xiuli Zuo

director of Qilu Hospital gastroenterology department

Shandong University

Eligibility Criteria

Inclusion Criteria

  • Participants, aged 18 years or older, who had not had a previous endoscopy were retrieved from all participating hospitals.

Exclusion Criteria

  • Not provided

Outcomes

Primary Outcomes

The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm.

Time Frame: 1 month

The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm.

Secondary Outcomes

  • The diagnostic sensitivity of gastrointestinal diseases with deep learning algorithm.(1 month)
  • The diagnostic specificity of gastrointestinal diseases with deep learning algorithm.(1 month)
  • The diagnostic positive predictive value of gastrointestinal diseases with deep learning algorithm.(1 month)
  • The diagnostic negative predictive value of gastrointestinal diseases with deep learning algorithm.(1month)

Study Sites (1)

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