Evaluation of AI-assisted diagnosis software for colonoscopy images.
Not Applicable
Recruiting
- Conditions
- Colonic epithelial lesion
- Registration Number
- JPRN-UMIN000044609
- Lead Sponsor
- Showa University Northern Yokohama Hospital
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Recruiting
- Sex
- All
- Target Recruitment
- 400
Inclusion Criteria
Not provided
Exclusion Criteria
1. Patients who refuse to participate. 2. Lesions in patients with inflammatory bowel disease in a broad sense 3. Lesions not captured by NBI imaging
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Sensitivity of AI for colonic adenoma (=<10mm)
- Secondary Outcome Measures
Name Time Method 1. Specificity, accuracy, NPV and PPV of AI for colonic adenoma (=<10mm) 2. Sensitivity, specificity, accuracy, NPV and PPV of AI for colonic non-neoplasms (=<10mm) 3. Sensitivity, specificity, accuracy, NPV and PPV of AI for colonic sesile serrated adenoma/polyp (=<10mm) 4. Sensitivity, specificity, accuracy, NPV and PPV of AI by the morphology of the lesions.