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Building of Prognosis Model for Patients With Cirrhosis Based on Sarcopenia Assessed by Deep Learning

NCT06531200 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2024-08-06

No results posted yet for this study

Summary

The goal of this observational study is to develop and validate a fully automated imaging deep learning platform for the evaluation of sarcopenia in liver cirrhosis. Based on this model, a new prognostic model for liver cirrhosis incorporating imaging biomarkers such as sarcopenia will be constructed, and its predictive performance will be validated.

Conditions

Sponsors & Collaborators

  • Peking University People's Hospital

    lead OTHER

Principal Investigators

  • Rui Huang, Dr. · Rui Huang, Dr. PekignUnviersity People's Hospital

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-09-01
Primary Completion
2025-08-31
Completion
2025-12-31

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06531200 on ClinicalTrials.gov