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Intelligent Diagnosis and Prognosis Prediction for Pediatric Hepatobiliary Diseases Using Multi-Source Biomedical Data

Intelligent Diagnosis and Prognosis Prediction for Pediatric Hepatobiliary Diseases Using Multi-Source Biomedical Data

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500111075
Enrollment
Unknown
Registered
2025-10-24
Start date
2025-10-27
Completion date
Unknown
Last updated
2025-10-27

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

Conditions

Pediatric Liver Disease/Cholestasis/Biliary Atresia/Hepatitis/Liver Fibrosis/Liver Cirrhosis/Liver Tumors

Interventions

Gold Standard:Needle biopsy or pathological biopsy
Index test:Image-Clinic Integrated AI Model

Sponsors

Guangzhou Women and Children Medical Center Liuzhou Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
No minimum to 18 Years

Inclusion criteria

Inclusion criteria: 1. Age <= 18 years; 2. Diagnosis of cholestasis, biliary atresia, hepatitis, liver fibrosis, liver cirrhosis, or liver tumors, confirmed by surgery and/or pathology; 3. Availability of complete MRI images with diagnostic quality; 4. Availability of complete serum laboratory indicators of liver function.

Exclusion criteria

Exclusion criteria: Patients without a definitive diagnosis

Design outcomes

Primary

MeasureTime frame
Liver Fibrosis Staging;Concordance index;Area Under the Curve;

Secondary

MeasureTime frame
Accuracy;Sensitivity;Specificity;

Countries

China

Contacts

Public ContactShuyi Liu

Guangzhou Women and Children Medical Center Liuzhou Hospital

lsyjnu@163.com+86 135 6018 5634

Outcome results

None listed

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