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development and validation of a machine learning model to evaluate the severity of liver cirrhosis

development and validation of an artifical intelligence model to predict the subclassification of liver cirrhosis

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300071030
Enrollment
Unknown
Registered
2023-04-28
Start date
2023-05-15
Completion date
Unknown
Last updated
2023-06-04

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

Conditions

liver cirrhosis

Interventions

Gold Standard:The Laennec staging system
Index test:CT images construct a ML model for subclassification of liver cirrhosis

Sponsors

Suzhou Ninth People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 100 Years

Inclusion criteria

Inclusion criteria: (1) age=18 years old (2) pathologic examination–confirmed liver cirrhosis (3) the interval between CT scanning and pathological reports less than 3 months (4) availability of clinical data and contrast-enhanced CT images.

Exclusion criteria

Exclusion criteria: (1) previous history of liver surgery (prior liver resection or transplantation) (2) the biopsy sample <10 mm in length

Design outcomes

Primary

MeasureTime frame
CT radiomics featues;Prothrombin time;Total bilirubin;Albumin;alanine transaminase;Aspartate aminotransferase;receiver operator characteristic curv;average marco;—

Secondary

MeasureTime frame
average micro;—

Countries

China

Contacts

Public Contactxiping shen

Suzhou Ninth People's Hospital

shenxiping2022@163.com+86 512 8882221

Outcome results

None listed

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