NCT05819099

The Role of Artificial Intelligence in Endoscopic Diagnosis of Esophagogastric Junctional Adenocarcinoma：A Single Center, Case-control, Diagnostic Study

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 200 (estimated)
• Sponsor: Qilu Hospital of Shandong University · Academic / Other
• Sex: All
• Age: 18 Years – 75 Years
• Healthy volunteers: Accepted

Summary

This is a single center, case-control, diagnostic study.The aim of this study is to use deep learning methods to retrospectively analyze the imaging data of gastrointestinal endoscopy in Qilu Hospital, and construct an artificial intelligence model based on endoscopic images for detecting and determining the depth of invasion of esophagogastric junctional adenocarcinoma.This study will also compare the established AI model with the diagnostic results of endoscopists to evaluate the clinical auxiliary value of the model for endoscopists.The research includes stages such as data collection and preprocessing, artificial intelligence model development, model testing and evaluation. The gastroscopy image dataset constructed by this research institute mainly includes three modes of endoscopic imaging: white light endoscopy, optical enhancement endoscopy (OE), and narrowband imaging endoscopy (NBI).

Conditions

• Stomach Neoplasms

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	An Intelligent Endoscopic Diagnosis System Developed and Verified Based on Deep Learning	This study will compare the established AI model with the diagnostic results of endoscopists to evaluate the clinical auxiliary value of the model for endoscopists.

Timeline

• Start date: 2023-12-01
• Primary completion: 2025-04-01
• Completion: 2026-04-01
• First posted: 2023-04-19
• Last updated: 2023-11-18