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Construction and validation of an artificial intelligence-based grading diagnostic model for follicular lymphoma

Construction and validation of an artificial intelligence-based grading diagnostic model for follicular lymphoma

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400094900
Enrollment
Unknown
Registered
2024-12-30
Start date
2025-01-01
Completion date
Unknown
Last updated
2025-01-06

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

Conditions

Follicular lymphoma

Interventions

Gold Standard:The FL grading results reviewed by three senior pathologists
Index test:AI grading diagnostic model follicular lymphoma.

Sponsors

The First Affiliated Hospital of Army Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
20 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1.Grade 1 and Grade 2 follicular lymphoma;

Exclusion criteria

Exclusion criteria: 1.cases with unclear diagnosis;The sections are too thick, overlapping, damaged, bubbly, wrinkled;Biopsy specimen;

Design outcomes

Primary

MeasureTime frame
Accuracy;Precision;Recall;AUC;—

Countries

China

Contacts

Public ContactMeng Gang

The First Affiliated Hospital of Army Medical University

1916587889@qq.com+86 13012368232

Outcome results

None listed

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