Deep Learning Algorithm for the Diagnosis of Gastrointestinal Diseases

Study Overview
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Brief Summary
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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
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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.

Official Title
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Development and Validation of a Deep Learning Algorithm for the Diagnosis of Gastrointestinal Diseases

Conditions
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Gastrointestinal Disease

Intervention / Treatment
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* Device: AI for the Diagnosis of Gastrointestinal Diseases


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Participants, aged 18 years or older, who had not had a previous endoscopy were retrieved from all participating hospitals. Exclusion Criteria: -

Ages Eligible for Study
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Minimum Age: 18 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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Design Details

Primary Purpose: Diagnostic
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: AI monitoring gastrointestinal endoscopy<br>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. | Device: AI for the Diagnosis of Gastrointestinal Diseases<br>* 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.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm. | The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm. | 1 month | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The diagnostic sensitivity of gastrointestinal diseases with deep learning algorithm. | The diagnostic sensitivity of gastrointestinal diseases with deep learning algorithm. | 1 month | 
| The diagnostic specificity of gastrointestinal diseases with deep learning algorithm. | The diagnostic specificity of gastrointestinal diseases with deep learning algorithm. | 1 month | 
| The diagnostic positive predictive value of gastrointestinal diseases with deep learning algorithm. | The diagnostic specificity of gastrointestinal diseases with deep learning algorithm. | 1 month | 
| The diagnostic negative predictive value of gastrointestinal diseases with deep learning algorithm. | The diagnostic specificity of gastrointestinal diseases with deep learning algorithm. | 1month | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Deep Learning, Central Neural Networks, Endoscopy, Gastrointestinal Disease