Connection Between Tongue Signs and Bile Reflux Analysed With Artificial Intelligence

Study Overview
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Brief Summary
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By introducing artificial intelligence into Chinese medicine tongue diagnosis, we collated and collected tongue images, anxiety and depression scales and gastroscopy reports, mined and analysed the correlation between tongue images and bile reflux and anxiety and depression and constructed a prediction model to analyse the possibility of predicting bile reflux and anxiety and depression in patients based on tongue images.

Detailed Description
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Firstly, after the patient signs the informed consent form, the researcher will collect pictures of the patient's tongue and obtain basic information about the patient. Second, the patients are scored on the Anxiety and Depression Scale. Thirdly, after the patient undergoes gastroscopy, the patient's gastroscopy report is obtained. Finally, the patient's tongue image, information and gastroscopy report are matched to construct an artificial intelligence model of tongue image and bile reflux and anxiety and depression, and the quality of the model is assessed.

Official Title
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Analysing the Link Between Tongue Signs and Bile Reflux by Artificial Intelligence

Conditions
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Artificial Intelligence, Tongue, Bile Reflux

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patients aged 18 to 80 years who wish to undergo gastroscopy. Patients have given their informed consent and signed the informed consent form. Exclusion Criteria: Serious heart, liver, kidney or other underlying illness, or mental illness. Patients taking anti-anxiety or depression medication within 3 months. Current H. pylori infection. History of surgery on the digestive or biliary tract. Peptic ulcer, malignant tumour of the digestive tract, etc. Patients taking bismuth or other staining medications. Pregnant or lactating women.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 80 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Bile Reflux Group<br>Gastroscopic reports of enrolled patients will be extracted and patients will be identified as having bile reflux according to Kellosalo J classification. Grade I: small amount of yellowish reflux emerging from the pyloric orifice and/or yellowish staining of the mucus lake, which is pale yellow in colour. Grade II: intermittent gush of reflux from the pyloric opening and/or yellowish staining of the mucus lake, which is dark yellow. Grade III: frequent gush of yellow-green reflux from the pyloric orifice and/or yellow-green mucus covering the stomach. | |
| Non-biliary reflux group<br>Gastroscopic reports will be extracted from patients enrolled in the group that do not meet the Kellosalo J classification as the non-biliary reflux group. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Sensitivity | Sensitivity of artificial intelligence models Sensitivity = number of true positives / (number of true positives + number of false negatives) * 100%. | 3 years | 
| Specificity | Specificity of Artificial Intelligence Models Specificity = number of true negatives / (number of true negatives + number of false positives)) *100% | 3 years | 
| Positive predictive values(PPV) | Positive predictive values from artificial intelligence models Positive predictive value = true positive / (true positive + false positive) *100% | 3 years | 
| Negative predictive values (NPV) | Negative predictive values for artificial intelligence models Negative Predictive Value = True Negative / (True Negative + False Negative) *100% | 3 years | 
| AUC (95% CI) | area under the receiver operating characteristic curve (AUC), | 3 years | 
| Accuracy | Accuracy for artificial intelligence models Accuracy = (true positives + true negatives) / total number of subjects * 100% | 3 years | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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artificial intelligence, tongue, bile reflux