Clinical trial NCT04811599: Deep Learning Algorithm for the Diagnosis of Gastrointestinal Diseases Depending on Tongue Images
Official title: Deep Learning Algorithm for the Diagnosis of Gastrointestinal Diseases Depending on Tongue Images
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Gastrointestinal Disease
Keywords: Gastrointestinal Disease
tongue image
artificial intelligence
deep learning
gastrointestinal flora
Lead sponsor: Shandong University
Sponsor class: OTHER
First posted: 2021-03-23
Enrollment: 2000
Sex: ALL
Minimum age (years): 18
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: OTHER
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients aged 18 - 80 years undergoing endoscopic examination

Brief 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.

Eligibility criteria: Inclusion Criteria:

* Patients aged 18 - 80 years undergoing endoscopic examination;patients gave informed consent and signed informed consent.

Exclusion Criteria:

-

Primary outcomes:
measure: The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm
timeFrame: 1 month
Secondary outcomes:
measure: The diagnostic sensitivity of gastrointestinal diseases with deep learning algorithm
timeFrame: 1 month
measure: The diagnostic specificity of gastrointestinal diseases with deep learning algorithm
timeFrame: 1 month
measure: The diagnostic positive predictive value of gastrointestinal diseases with deep learning algorithm
timeFrame: 1 month
measure: The diagnostic negative predictive value of gastrointestinal diseases with deep learning algorithm
timeFrame: 1 month
Other outcomes:
Locations:
city: Jinan
country: China
facility: Qilu Hospital, Shandong University
state: Shandong
Study officials:
affiliation: Study Principal investigator
name: Xiuli Zuo, MD,PhD
role: STUDY_CHAIR
References: