Deep Learning Algorithm for the Diagnosis of Gastrointestinal Diseases

Not Applicable

• Conditions: Gastrointestinal Disease
• Interventions: Device: AI for the Diagnosis of Gastrointestinal Diseases

• Registration Number: NCT04222439
• Lead Sponsor: Shandong University

Brief Summary

The purpose of this study is to develop and validate a deep learning algorithm for the diagnosis of gastrointestinal diseases. Then, evaluate the accuracy this new artificial intelligence(AI) assisted recognition system in clinic practice.

Detailed Description

Recently, deep learning algorithm based on central neural networks (CNN) has shown multiple potential in computer-aided detection and computer-aided diagnose of gastrointestinal lesions. However, there is still a blank in recognition of all gastrointestinal diseases. This study aim to develop and validate a deep learning algorithm for the diagnosis of gastrointestinal diseases. Then, evaluate the accuracy this new artificial intelligence(AI) assisted recognition system in clinic practice.

Study Timeline

• Study Start: 2020-01-01
• Study First Submitted: 2020-01-07
• Study First Submitted QC: 2020-01-07
• Study First Posted: 2020-01-10
• Status Verified: 2020-02
• Primary Completion: 2020-02
• Study Completion: 2020-02
• Last Update Submitted: 2020-02-14
• Last Update Posted: 2020-02-18

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 100000

Inclusion Criteria

• Participants, aged 18 years or older, who had not had a previous endoscopy were retrieved from all participating hospitals.

Exclusion Criteria

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Arm && Interventions

Group	Intervention	Description
AI monitoring gastrointestinal endoscopy	AI for the Diagnosis of Gastrointestinal Diseases	After receiving standard preparation regimen, patients go through colonoscopy or gastroscopy under the AI monitoring device. The whole procedure is monitored by AI associated recognition system. Gastrointestinal diseases will be detect and diagnosis in which the AI device will automatically captured relevant images and report the site of each segment on the screen. Histology analysis is set as a golden standard. Then all the AI captured images will be reviewed by human group, which consists of three to five experienced endoscopic physicians.

Primary Outcome Measures

Name	Time	Method
The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm.	1 month	The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm.

Secondary Outcome Measures

Name	Time	Method
The diagnostic sensitivity of gastrointestinal diseases with deep learning algorithm.	1 month	The diagnostic sensitivity of gastrointestinal diseases with deep learning algorithm.
The diagnostic specificity of gastrointestinal diseases with deep learning algorithm.	1 month	The diagnostic specificity of gastrointestinal diseases with deep learning algorithm.
The diagnostic positive predictive value of gastrointestinal diseases with deep learning algorithm.	1 month	The diagnostic specificity of gastrointestinal diseases with deep learning algorithm.
The diagnostic negative predictive value of gastrointestinal diseases with deep learning algorithm.	1month	The diagnostic specificity of gastrointestinal diseases with deep learning algorithm.

Trial Locations

Locations (1)

Qilu Hospital, Shandong University; 🇨🇳 Jinan, Shandong, China