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Clinical Trial Summary

This is an artificial intelligence-based optical artificial intelligence assisted system that can assist endoscopists in improving the quality of endoscopy.


Clinical Trial Description

Endoscopic diagnosis and treatment play an important role in the discovery and treatment of gastrointestinal diseases.With the rapid increase in the number of endoscopies, the workload of endoscopists increases further.The high workload reduces the quality of endoscopy, leading to incomplete coverage and incomplete detection of lesions.With the rapid increase in the number of endoscopies, the workload of endoscopists increases further.The high workload reduces the quality of endoscopy, leading to incomplete coverage and incomplete detection of lesions.Therefore, carrying out deep learning and other artificial intelligence methods has good academic research and practical value for improving the quality of endoscopic diagnosis and treatment.The research and development, testing and functional evaluation of artificial intelligence devices need to use a large number of endoscopic images, and at the same time, the effectiveness and safety of artificial intelligence devices need to be verified in different hospitals and environments.Based on this, our research group intends to collect endoscopic image data from different hospitals for training and validation of the model. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT04232462
Study type Observational
Source Renmin Hospital of Wuhan University
Contact
Status Active, not recruiting
Phase
Start date January 1, 2020
Completion date December 31, 2025

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