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UnknownNCT04811599

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

Status
Unknown
Phase
Study type
Observational
Enrollment
2,000 (estimated)
Sponsor
Shandong University · Academic / Other
Sex
All
Age
18 Years – 80 Years
Healthy volunteers
Accepted

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.

Detailed 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.

Conditions

Timeline

Start date
2021-03-21
Primary completion
2022-06-01
Completion
2022-06-01
First posted
2021-03-23
Last updated
2021-03-23

Locations

1 site across 1 country: China

Source: ClinicalTrials.gov record NCT04811599. Inclusion in this directory is not an endorsement.