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Construction of an artificial intelligence model for endoscopic classification of chronic atrophic gastritis

Construction of an artificial intelligence model for endoscopic classification of chronic atrophic gastritis

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400082729
Enrollment
Unknown
Registered
2024-04-07
Start date
2024-04-12
Completion date
Unknown
Last updated
2024-04-08

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

Conditions

chronic atrophic gastritis

Interventions

endoscopic images:None

Sponsors

The First Affiliated Hospital of the Army Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: ? Patients who meet the diagnosis of chronic atrophic gastritis and have made Kimura-Takemoto classification ? The age of the patient is greater than or equal to 18 years ? Complete intracavitary pictures or video data of patients are kept in the endoscopic system ? Endoscopists can accurately identify the location of the patient's images and accurately determine whether there is gastric mucosal atrophy, and the gastric mucosal fold is fully exposed

Exclusion criteria

Exclusion criteria: The images of selected patients have poor clarity, blurred images, or image quality less than 1080P

Design outcomes

Primary

MeasureTime frame
success of construction;—

Countries

China

Contacts

Public ContactChen Lei

The First Affiliated Hospital of the Army Medical University

chenlei1977603@126.com+86 132 2868 3896

Outcome results

None listed

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