NCT04216901

A Single Center Study on the Effectiveness and Safety of Polyp Classification With Artificial Intelligence

A Single Center Study on the Effectiveness and Safety of Polyp Detection and Polyp Classification With Artificial Intelligence

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 70 (estimated)
• Sponsor: Renmin Hospital of Wuhan University · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: —

Summary

This is an artificial intelligence-based optical endoscopic polyp diagnosis system that can assist endoscopic doctors in diagnosing polyps and improve the quality of training in clinical Settings.

Detailed description

Large sessile and laterally spreading colorectal lesions(LSLs) are increasingly encountered during colonoscopy. LSLs have an increased risk of harbouring invasive cancer and can be challenging to excise endoscopically. Wide-field endoscopic mucosal resection (WF-EMR) is widely used in treating LSLs. In the East, meanwhile endoscopic submucosal dissection (ESD) is the dominant technique due to its ability to achieve en bloc resection in over 80% of cases. Many papers have demonstrated that selective-esd has the highest economic benefit. The key is to find a reliable way to select.

Conditions

• Colonic Diseases
• Artificial Intelligence

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Endoscopists refer to AI for diagnosis	The AI will provide a pathological prediction of the lesion during colonoscopy.

Timeline

• Start date: 2019-12-24
• Primary completion: 2020-12-31
• Completion: 2021-06-30
• First posted: 2020-01-03
• Last updated: 2020-10-20

Locations

1 site across 1 country: China