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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| deep learning algorithm group | Before patients going through colonoscopy or gastroscopy ,taking them tongue images and collecting basic information by mobile phone with Anymed.After examination,endoscopic report and histology analysis is collected .Categorizing the images by gastrointestinal diseases，developing and validating a deep learning algorithm for the diagnosis of digestive tract diseases depending on tongue images.Extracting tougue coating,gastric mucosa and stool DNA by high-throughput sequencing,and analyzing their composation,adundance and diversity. |
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| Measure | Description | Time Frame |
|---|---|---|
| The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm | The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm. | 1 month |
| Measure | Description | Time Frame |
|---|---|---|
| The diagnostic sensitivity of gastrointestinal diseases with deep learning algorithm | The diagnostic sensitivity of gastrointestinal diseases with deep learning algorithm. | 1 month |
| The diagnostic specificity of gastrointestinal diseases with deep learning algorithm |
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Inclusion Criteria:
Exclusion Criteria:
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Patients aged 18 - 80 years undergoing endoscopic examination
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| Name | Affiliation | Role |
|---|---|---|
| Xiuli Zuo, MD,PhD | Study Principal investigator | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Qilu Hospital, Shandong University | Jinan | Shandong | 250012 | China |
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| ID | Term |
|---|---|
| D005767 | Gastrointestinal Diseases |
| ID | Term |
|---|---|
| D004066 | Digestive System Diseases |
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tougue coating,gastric mucosa and stool sample
The diagnostic specificity of gastrointestinal diseases with deep learning algorithm |
| 1 month |
| The diagnostic positive predictive value of gastrointestinal diseases with deep learning algorithm | The diagnostic specificity of gastrointestinal diseases with deep learning algorithm | 1 month |
| The diagnostic negative predictive value of gastrointestinal diseases with deep learning algorithm | The diagnostic specificity of gastrointestinal diseases with deep learning algorithm | 1 month |