Prediction for quality of bowel preparation analyzing stool pictures via deep learning system

Status

Active, not recruiting

Phases

Unknown

Study type

Interventional

Source

CRIS

Registry ID

KCT0008980

Enrollment

5000

Registered

2023-11-24

Start date

2023-11-06

Completion date

Unknown

Last updated

2023-12-19

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

None listed

Interventions

Others(Deep learning system for the prediction of bowel preparation through the last stool photo before bowel preparation) : After bowel preparation for colonoscopy, a photo is taken of the last stool

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: A patient over the age of 18 who is scheduled for colonoscopy due to various indications, and whose entire colon can be observed

Exclusion criteria

Exclusion criteria: - Patients who do not agree to participate - Patients in whom it is difficult to observe the entire colon due to colectomy, etc. - Patients with inflammatory bowel disease

Design outcomes

Primary

Measure	Time frame
Accuracy of deep learning system via stool picture for the prediction of bowel preparation	—

Secondary

Measure	Time frame
Accuracy of deep learning system via stool picture for the prediction of bowel preparation in each bowel segment	—

Countries

Korea, Republic of

Contacts

Public ContactHa Lin Kwon

Yeongnam University Medical Center

img04@ymc.yu.ac.kr+82-53-620-3897

Outcome results