AI-Assisted Colonoscopy
DeviceAI can not only detect suspicious lesions timely, and label them in the field of view of the colonoscopy, but also monitor withdrawal speed and calculate the clean withdrawal time automatically.
NCT Number: NCT05941689
This is a randomized controlled multicenter clinical trial of computer-aided detection (CADe) system for the adjuvant diagnosis of intestinal polyps/adenomas ever conducted in a Chinese population. In addition, this study will evaluate the effect of CADe system on adenoma detection of endoscopists under fatigue.
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Notify Me18 year–85 year
All sexes
Interventional
Not applicable
Xiangya Hospital Central South University, Changsha, Hunan, China
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Patients who need to undergo colonoscopy. -
Exclusion criteria
Patients with CRC, inflammatory bowel disease, previous colonic resection, and antithrombotic therapy precluding polyp resection were excluded.
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AI can not only detect suspicious lesions timely, and label them in the field of view of the colonoscopy, but also monitor withdrawal speed and calculate the clean withdrawal time automatically.
Time frame: up to 2months
The proportion of patients with at least one histologically proven adenoma or carcinoma
Time frame: up to 2months
The proportion of patients with clean withdrawal time >6min.
Time frame: up to 2 months
The proportion of patients with at least one polyp.
Time frame: up to 2 months
The number of adenomas detected per colonoscopy
Time frame: up to 2 months
The number of polys detected per colonoscopy
Xiangya Hospital of Central South University
Other
Research on the Auxiliary Diagnosis and Treatment System of Digestive Endoscopy Based on Artificial Intelligence: An Efficacy Study of Artificial Intelligence-assisted Colonic Polyp Detection System
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