Ulcerative Colitis Mayo Score With Artificial Intelligence
Research on Artificial Intelligence-based Mayo Score Recognition System for Disease Activity Degree of Ulcerative Colitis Under Digestive Endoscopy
1 other identifier
observational
500
1 country
1
Brief 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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Apr 2022
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
February 27, 2022
CompletedStudy Start
First participant enrolled
April 1, 2022
CompletedFirst Posted
Study publicly available on registry
April 20, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2022
CompletedStudy Completion
Last participant's last visit for all outcomes
June 1, 2023
CompletedApril 20, 2022
April 1, 2022
8 months
February 27, 2022
April 14, 2022
Conditions
Outcome Measures
Primary Outcomes (1)
The accuracy of deep learning model in the training and validation datasets assessment of Mayo score in ulcerative colitis patients.
In the training and validation datasets, we plotted the AUC (area under curve) for Mayo 0, Mayo 1, Mayo 2, and Mayo 3 to evaluate our model objectively.
Through study completion, an average of 1 year.
Secondary Outcomes (1)
The accuracy and time efficiency of endoscopists assessment of Mayo score in ulcerative colitis patients.
Through study completion, an average of 1 year.
Eligibility Criteria
The images were retrieved from the endoscopy database of Army Medical Center of PLA and obtained from the colonoscopy of patients with ulcerative colitis who met the inclusion criteria. The data images were used to establish and verify the model of ai-assisted recognition system.
You may qualify if:
- Subjects were 18-72 years old, male and female;
- Clinical diagnosis of ulcerative colitis;
- The subjects underwent colonoscopy and the colonoscopy report was complete.
You may not qualify if:
- Subjects are younger than 18 years old or older than 72 years old;
- Subjects underwent colectomy, ileostomy, colostomy, ileostomy, or other intestinal resection;
- subjects with ambiguous diagnosis.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Third Military Medical University
Chongqing, Chongqing Municipality, 400042, China
Related Publications (1)
Qi J, Ruan G, Ping Y, Xiao Z, Liu K, Cheng Y, Liu R, Zhang B, Zhi M, Chen J, Xiao F, Zhao T, Li J, Zhang Z, Zou Y, Cao Q, Nian Y, Wei Y. Development and validation of a deep learning-based approach to predict the Mayo endoscopic score of ulcerative colitis. Therap Adv Gastroenterol. 2023 May 22;16:17562848231170945. doi: 10.1177/17562848231170945. eCollection 2023.
PMID: 37251086DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- STUDY DIRECTOR
Yanling Wei, Professor
Third Military Medical University
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Associate chief physician, M D.
Study Record Dates
First Submitted
February 27, 2022
First Posted
April 20, 2022
Study Start
April 1, 2022
Primary Completion
December 1, 2022
Study Completion
June 1, 2023
Last Updated
April 20, 2022
Record last verified: 2022-04