Ulcerative Colitis Mayo Score With Artificial Intelligence

Status Not yet recruiting

Clinical Trial Summary

This project will use deep learning to classify colonoscopy images of different severity of ulcerative colitis, so as to assist clinicians in the accurate diagnosis of ulcerative colitis.

Clinical Trial Description

In this project, artificial intelligence was used to colonoscopic images of patients with ulcerative colitis with different disease activity levels and classify them according to the evaluation standard Mayo score to assist endoscopists in identifying disease activity levels of patients with ulcerative colitis during colonoscopy. It can help clinical endoscopists to accurately identify, and the visualization technology of artificial intelligence category response map can comprehensively display the areas with high importance for deep network classification results, and visualize the experimental lesion sites, thus effectively verifying the reliability and interpretability of deep network. This study can provide strong support for accurate identification of disease activity in clinical ulcerative colitis, effectively reduce the workload of clinicians, and provide a convenient, effective and practical clinical teaching tool. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details

NCT number	NCT05336773
Study type	Observational
Source	Third Military Medical University
Contact	Yanling Wei, professor
Phone	+8615310354666
Email	lingzi016@tmmu.edu.cn
Status	Not yet recruiting
Phase
Start date	April 2022
Completion date	June 2023

View Details

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