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the impact of a computer aided diagnosis system based on deep learning on incresing polyp detection rate during colonoscopy, a prospective double blind study

the impact of a computer aided diagnosis system based on deep learning on incresing polyp detection rate during colonoscopy, a prospective double blind study

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
ChiCTR
Registry ID
ChiCTR1800017675
Enrollment
Unknown
Registered
2018-08-08
Start date
2018-09-03
Completion date
Unknown
Last updated
2019-08-27

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

Conditions

colon polyp

Interventions

Group 1:CAD system detect polyps in real time
Group 2:routine colonoscopy

Sponsors

Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
14 Years to 90 Years

Inclusion criteria

Inclusion criteria: consecutive patients to undergo colonoscopy

Exclusion criteria

Exclusion criteria: 1. With history of inflammatory bowel disease and highly suspected cases during colonoscopy examination; 2. With history of adenoma polyposis and highly suspected cases during colonoscopy examination; 3. With history of colorectal cancer and highly suspected cases during colonoscopy examination; 4. With history of colon surgery; 5. With contradiction of biopsy; 6. failed procedure to insertion to cecum.

Design outcomes

Primary

MeasureTime frame
adenoma detection rate;—

Secondary

MeasureTime frame
average number of detected polyps per colonoscopy;average number of detected adenoma per colonoscopy;polyp detection rate;—

Countries

China

Contacts

Public ContactPu Wang

Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital

360649580@qq.com+86 13688060588

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 28, 2026