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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT04384575
Other study ID # PX2020047
Secondary ID
Status Completed
Phase
First received
Last updated
Start date February 22, 2020
Est. completion date May 1, 2022

Study information

Verified date November 2023
Source Peking University
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

This study aims to construct a real-time quality monitoring system based on artificial intelligence technology.


Description:

Gastroscopy plays an important role in the detection and diagnosis of upper gastrointestinal diseases. It is necessary for endoscopists to operate gastroscope according to the standardized process, in order to avoid missing early lesions. However, with the rapid increase in the number of endoscopies, the workload of endoscopists increases further. High workload reduces the quality of endoscopy, resulting in incomplete observation of anatomical parts that are easy to be missed in the process of gastroscopy. There are significant differences in the operation level of different endoscopists. Therefore, carrying out artificial intelligence methods has good academic research and practical value for improving the quality of endoscopic diagnosis and treatment. Artificial intelligence devices need to use a large number of endoscopic images, based on this, we intends to collect endoscopic image data from our hospitals for training and validation of the model.


Recruitment information / eligibility

Status Completed
Enrollment 1570
Est. completion date May 1, 2022
Est. primary completion date January 13, 2022
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years to 75 Years
Eligibility Inclusion Criteria: 1. Patiens aged 18 years or above undergoing gastroscopy; 2. Be able to read, understand and sign informed consent; Exclusion Criteria: 1. Patients with absolute contraindications to endoscopy examination; 2. pregnant women; 3. previous history of gastric surgery; 4. the researcher considers that the subject is not suitable for clinical trial.

Study Design


Related Conditions & MeSH terms


Intervention

Diagnostic Test:
blind spots
missed part during map the entire stomach through endoscopy

Locations

Country Name City State
China Beijing Cancer Hospital Beijing Haidian

Sponsors (1)

Lead Sponsor Collaborator
Peking University

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary Accuracy Calculate the accuracy of AI's judgment on images 2020.2.22-2020.7.1
Primary Sensitivity number of images in which AI correctly diagnosed positive/all images with positive 2020.2.22-2020.7.1
Primary Specificity number of images in which AI correctly diagnosed negative/all images negative 2020.2.22-2020.7.1
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