The Potential Value and Impact of Diagnostic Biomarkers for MAFLD Using Machine Learning Methods

NCT06061640 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 500

Last updated 2023-09-29

No results posted yet for this study

Summary

This is a case-control study that aims to build a predictive model for MAFLD based on machine learning.

Conditions

  • Metabolic Dysfunction-associated Fatty Liver Disease

Sponsors & Collaborators

  • Zhejiang Chinese Medical University

    collaborator OTHER_GOV
  • The First Affiliated Hospital of Zhejiang Chinese Medical University

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-06-01
Primary Completion
2024-06-30
Completion
2024-12-31

Countries

  • China

Study Locations

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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 NCT06061640 on ClinicalTrials.gov