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Liver Cirrhosis Diagnosis Prioritizing Algorithm Based on Electronic Health Records.

NCT05218538 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 120

Last updated 2022-03-31

No results posted yet for this study

Summary

The investigators use machine learning capabilities on massive electronic health records for the purpose of developing a model that prioritizes individuals at high risk of progressing to liver cirrhosis, and validating it with participants that the model found to be at high risk.

constructing and validating a reliable model, with sufficient accuracy to justify further and expensive means of detection, will enable treating patients with damaged liver at an early enough stage to allow improvement of the liver condition.

Conditions

  • NAFLD - Nonalcoholic Fatty Liver Disease
  • Fibrosis, Liver
  • Cirrhosis, Liver

Interventions

DIAGNOSTIC_TEST

Fibroscan (non interventional)

An elastography test that includes an ultrasound wave imaging of the liver to estimate liver fatness, in combination with a proprioty examination of the liver stiffness.

Sponsors & Collaborators

  • Weizmann Institute of Science

    collaborator OTHER

  • HaEmek Medical Center, Israel

    lead OTHER

Principal Investigators

  • Ziv Neeman, MD · HaEmek Medical Center, Israel

Eligibility

Min Age
40 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-03-15
Primary Completion
2023-08-31
Completion
2023-12-31

Countries

  • Israel

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 NCT05218538 on ClinicalTrials.gov