Deep Learning Algorithm for the Diagnosis of Gastrointestinal Diseases

NCT04222439 | Unknown DMC

• 1 other identifier: 2019-SDU-QILU-G710
• Study Type: interventional
• Target: 100,000
• Locations: 1 country
• Sites: 1

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.

Conditions

Gastrointestinal Disease

Keywords

Deep Learning; Central Neural Networks; Endoscopy; Gastrointestinal Disease

Outcome Measures

Primary Outcomes (1)

• The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm.

  The diagnostic accuracy of gastrointestinal diseases with deep learning algorithm.

  1 month

Secondary Outcomes (4)

• The diagnostic sensitivity 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

• The diagnostic negative predictive value of gastrointestinal diseases with deep learning algorithm.

  1month

Study Arms (1)

AI monitoring gastrointestinal endoscopy

EXPERIMENTAL

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

Interventions

AI for the Diagnosis of Gastrointestinal Diseases DEVICE

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.

AI monitoring gastrointestinal endoscopy

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

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

Sponsors & Collaborators

• Shandong University: lead

Study Sites (1)

Qilu Hospital, Shandong University

Jinan, Shandong, 250012, China

RECRUITING

MeSH Terms

Conditions

Gastrointestinal Diseases

Condition Hierarchy (Ancestors)

Digestive System Diseases

Study Officials

• Xiuli Zuo, MD,PhD

  Qilu Hospital of Shandong University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Xiuli Zuo, MD,PhD

CONTACT

15588818685; zuoxiuli@sdu.edu.cn

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: director of Qilu Hospital gastroenterology department

Study Record Dates

• First Submitted: January 7, 2020
• First Posted: January 10, 2020
• Study Start: January 1, 2020
• Primary Completion: February 1, 2020
• Study Completion: February 1, 2020
• Last Updated: February 18, 2020

Record last verified: 2020-02

Locations

CN (1)