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临床试验/NCT04811599
NCT04811599Unknown不适用

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

Shandong University1 个研究点 分布在 1 个国家目标入组 2,000 人开始时间: 2021年3月21日最近更新:
适应症

试验速览

阶段
不适用
发起方
入组人数
2,000
试验地点
1
主要终点
The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm

研究概览

简要总结

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.

详细描述

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.

研究设计

研究类型
Observational
观察模型
Other
时间视角
Prospective

入排标准

年龄范围
18 Years 至 80 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

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

排除标准

  • 未提供

结局指标

主要结局

The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm

时间窗: 1 month

The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm.

次要结局

  • The diagnostic sensitivity of gastrointestinal diseases with deep learning algorithm(1 month)
  • The diagnostic negative predictive value of gastrointestinal diseases with deep learning algorithm(1 month)
  • The diagnostic specificity of gastrointestinal diseases with deep learning algorithm(1 month)
  • The diagnostic positive predictive value of gastrointestinal diseases with deep learning algorithm(1 month)

研究者

发起方
Shandong University
申办方类型
Other
责任方
Principal Investigator
主要研究者

Xiuli Zuo

Director of Qilu Hospital gastroenterology department

Shandong University

研究点 (1)

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