Connection Between Tongue Signs and Bile Reflux Analysed With Artificial Intelligence

Artificial Intelligence Clinical Trial

Official title:

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

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT05369572
• Other study ID #: 2022SDU-QILU-G002
• Status: Not yet recruiting
• Start date: June 30, 2022
• Est. completion date: June 30, 2025

Study information

• Verified date: June 2022
• Source: Shandong University
• Contact: Xiuli Zuo, MD, PhD
• Phone: 86 15588818685
• Email: zuoxiuli[@]sdu.edu.cn
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

Description:

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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 1500
• Est. completion date: June 30, 2025
• Est. primary completion date: June 30, 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 80 Years

Eligibility

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.

Related Conditions & MeSH terms

• Artificial Intelligence
• Bile Reflux
• Gastroesophageal Reflux

Locations

Country	Name	City	State
China	Qilu hosipital	Jinan	Shandong

Sponsors (1)

Lead Sponsor	Collaborator
Shandong University

Country where clinical trial is conducted

China, 

Outcome

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