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Deep Learning Algorithm for the Diagnosis of Gastrointestinal Diseases Depending on Tongue Images

Gastrointestinal Disease Clinical Trial

Official title:
Deep Learning Algorithm for the Diagnosis of Gastrointestinal Diseases Depending on Tongue Images

Clinical Trial Summary

The purpose of this study is to analysize the relationship between the characteristics of tongue image and the diagnosis of gastrointestinal diseases , then develop and validate a deep learning algorithm for the diagnosis of gastrointestinal diseases depending on tongue images, so as to improve the objectiveness and intelligence of tongue diagnosis. At the same time, gastrointestinal flora of common tongue images were analyzed in order to provide a microecological basis for understanding the relationship between tongue images and digestive tract diseases.

Clinical Trial Description

Tongue diagnosis is an important part of traditional Chinese medicine.According to traditional Chinese medicine theory,health condition can assessed by observing tougue features,including color, gloss, shape and coating of the tongue, tongue features reflect gastric mucosal state, disease classification and prognosis. Recently, deep learning based on central neural networks (CNN) has shownTongue diagnosis is an important part of traditional Chinese medicine.According to traditional Chinese medicine theory,health condition can assessed by observing tougue features,including color, gloss, shape and coating of the tongue, tongue features reflect gastric mucosal state, disease classification and prognosis. Recently, deep learning based on central neural networks (CNN) has shown multiple potential in detecting and diagnosing gastrointestinal diseases. However, there is still a blank in recognition of gastrointestinal diseases .This study aims to develop and validate a deep learning algorithm for the diagnosis of digestive tract diseases depending on tongue images,and analyze gastrointestinal flora of common tongue images. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT04811599
Study type Observational
Source Shandong University
Contact
Status Enrolling by invitation
Phase
Start date March 21, 2021
Completion date June 1, 2022
View Details
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