Ulcerative Colitis Mayo Score With Artificial Intelligence

Study Purpose

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.

Recruitment Criteria

Accepts Healthy Volunteers

Healthy volunteers are participants who do not have a disease or condition, or related conditions or symptoms

Yes
Study Type

An interventional clinical study is where participants are assigned to receive one or more interventions (or no intervention) so that researchers can evaluate the effects of the interventions on biomedical or health-related outcomes.


An observational clinical study is where participants identified as belonging to study groups are assessed for biomedical or health outcomes.


Searching Both is inclusive of interventional and observational studies.

Observational
Eligible Ages 18 Years - 72 Years
Gender All
More Inclusion & Exclusion Criteria

Inclusion Criteria:

1. Subjects were 18-72 years old, male and female; 2. Clinical diagnosis of ulcerative colitis; 3. The subjects underwent colonoscopy and the colonoscopy report was complete.

Exclusion Criteria:

1. Subjects are younger than 18 years old or older than 72 years old; 2. Subjects underwent colectomy, ileostomy, colostomy, ileostomy, or other intestinal resection; 3. subjects with ambiguous diagnosis.

Trial Details

Trial ID:

This trial id was obtained from ClinicalTrials.gov, a service of the U.S. National Institutes of Health, providing information on publicly and privately supported clinical studies of human participants with locations in all 50 States and in 196 countries.

NCT05336773
Phase

Phase 1: Studies that emphasize safety and how the drug is metabolized and excreted in humans.

Phase 2: Studies that gather preliminary data on effectiveness (whether the drug works in people who have a certain disease or condition) and additional safety data.

Phase 3: Studies that gather more information about safety and effectiveness by studying different populations and different dosages and by using the drug in combination with other drugs.

Phase 4: Studies occurring after FDA has approved a drug for marketing, efficacy, or optimal use.

Lead Sponsor

The sponsor is the organization or person who oversees the clinical study and is responsible for analyzing the study data.

Third Military Medical University
Principal Investigator

The person who is responsible for the scientific and technical direction of the entire clinical study.

Yanling Wei, Professor
Principal Investigator Affiliation Third Military Medical University
Agency Class

Category of organization(s) involved as sponsor (and collaborator) supporting the trial.

Other
Overall Status Not yet recruiting
Countries China
Conditions

The disease, disorder, syndrome, illness, or injury that is being studied.

Ulcerative Colitis, Colonoscopy, Deep Learning
Additional Details

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.

Contact a Trial Team

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International Sites

Third Military Medical University, Chongqing, Chongqing, China

Status

Address

Third Military Medical University

Chongqing, Chongqing, 400042

Site Contact

Yanling Wei, Professor

lingzi016@126.com

15310354666

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