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Development and validation of machine learning model for quantitative analysis of liver fibrosis

Development and validation of a machine learning system for quantification of liver fibrosis using Masson's trichrome staining images

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2100043695
Enrollment
Unknown
Registered
2021-02-27
Start date
2021-02-28
Completion date
Unknown
Last updated
2021-06-22

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

Conditions

liver fibrosis

Interventions

Gold Standard:Paraffin pathological diagnosis results and Collagen proportionate area results
Index test:Medical&#32
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Sponsors

Renji Hospital Affiliated to Medical College of Shanghai Jiaotong University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Patients over 18 years old; 2. Patients with pathological reports including liver fibrosis stage.

Exclusion criteria

Exclusion criteria: 1. Patients with incomplete clinical data; 2. Patients who could not get CT images; 3. Patients whose liver tissue is insufficient for fibrosis staging.

Design outcomes

Primary

MeasureTime frame
Collagen proportionate area;—

Secondary

MeasureTime frame
Pathological diagnosis of paraffin ;—

Countries

China

Contacts

Public ContactFeng Xue

Renji Hospital Affiliated to Medical College of Shanghai Jiaotong University

fengxue6879@163.com+86 13701813929

Outcome results

None listed

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