Artificial intelligence-assisted colonoscopy for real-time diagnosis of colorectal lesion classification: a prospective, multicenter clinical study

Status

Active, not recruiting

Phases

Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2200058831

Enrollment

Unknown

Registered

2022-04-17

Start date

2022-05-06

Completion date

Unknown

Last updated

2024-01-22

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

Conditions

Colorectal polyps

Interventions

Gold Standard:Pathological diagnosis

Index test:AI real-time diagnostic software (NICE classification,JNET classification,pit pattern classification)

Eligibility

Sex/Gender

All

Age

18 Years to 75 Years

Inclusion criteria

Inclusion criteria: 1. Subjects sign the informed consent form voluntarily; 2. Subjects aged 18-75 years old; 3. Subjects who undergo colonoscopy.

Exclusion criteria

Exclusion criteria: 1. Subjects are not fit for endoscopy; 2. The quality of the subjects' endoscopic images does not meet the requirements; 3. Subjects who judge by the researchers to be unsuitable for this trial.

Design outcomes

Primary

Measure	Time frame
Diagnostic accuracy;Diagnostic specificity;Diagnostic sensitivity;	—

Secondary

Measure	Time frame
AI to determine the accuracy of polyp histology;	—

Countries

China

Contacts

Public ContactSide Liu

Nanfang Hospital, Southern Medical University

liuside2011@163.com+86 13902212459

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026