Personalized diagnosis of early colorectal cancer high-risk population based on colonoscopy machine learning model

Status

Active, not recruiting

Phases

Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2200061105

Enrollment

Unknown

Registered

2022-06-15

Start date

2022-06-02

Completion date

Unknown

Last updated

2023-03-26

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

Conditions

Early colorectal cancer

Interventions

Gold Standard:Pathological diagnosis of resected intact sample.

Index test:Artificial&#32

intelligent&#32

convolution&#32

neural&#32

network

Eligibility

Sex/Gender

All

Age

50 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1.High risk factors for intestinal tumors:(1) First-degree relatives with colorectal cancer;(2) Age >50 years old;(3) Male;(4) Smoking;(5) Body mass index >=23 kg/m2;(6) Diabetes; Anyone with any one of (1) and (2)-(6) or any three of (2)-(6), and no previous colonoscopy; 2.The patient agrees and can cooperate with the examination, and signs the informed consent form; 3. The picture under colonoscopy is clear.

Exclusion criteria

Exclusion criteria: 1.Colon cancer has been confirmed before colonoscopy; 2.Colonoscopy shows non-adenoma and early colorectal cancer; 3.The image quality is poor, which seriously affects computer analysis and learning; 4.Case data are seriously missing or fail to meet the inclusion criteria; 5.Other conditions that the researcher thought should not be included in the study.

Design outcomes

Primary

Measure	Time frame
Colonoscopic images;	—

Countries

China

Contacts

Public ContactShi Jihua

shijihua1981@sina.com+86 15811172318

Outcome results

None listed

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