Status:
UNKNOWN
Deep Learning Algorithm for Recognition of Colonic Segments.
Lead Sponsor:
Shandong University
Conditions:
Colonic Diseases
Eligibility:
All Genders
18-70 years
Phase:
NA
Brief Summary
The purpose of this study is to develop and validate a deep learning algorithm to realize automatic recognition of colonic segments under conventional colonoscopy. Then, evaluate the accuracy this new...
Detailed Description
Colonoscopy is recommended as a routine examination for colorectal cancer screening. Complete inspection of all colon segments is the basis of colonoscopy quality control, and furthermore improves the...
Eligibility Criteria
Inclusion
- Patients aged 18-70 years undergoing conventional colonoscopy
Exclusion
- Known or suspected bowel obstruction, stricture or perforation
- Compromised swallowing reflex or mental status
- Severe chronic renal failure(creatinine clearance \< 30 ml/min)
- Severe congestive heart failure (New York Heart Association class III or IV)
- Uncontrolled hypertension (systolic blood pressure \> 170 mm Hg, diastolic blood pressure \> 100 mm Hg)
- Dehydration
- Disturbance of electrolytes
- Pregnancy or lactation
- Hemodynamically unstable
- Unable to give informed consent
Key Trial Info
Start Date :
September 15 2019
Trial Type :
INTERVENTIONAL
Allocation :
ESTIMATED
End Date :
December 15 2019
Estimated Enrollment :
60 Patients enrolled
Trial Details
Trial ID
NCT04087824
Start Date
September 15 2019
End Date
December 15 2019
Last Update
September 12 2019
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