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Diagnosis and Characterization of Non-Alcoholic Fatty Liver Disease Based on Artificial Intelligence.

NCT04099147 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 14046

Last updated 2019-09-23

No results posted yet for this study

Summary

A key element in the diagnosis of non-alcoholic fatty liver disease (NAFLD) is the differentiation of non-alcoholic steatohepatitis (NASH) from non-alcoholic fatty liver (NAFL) and the staging of the liver fibrosis, given that patients with NASH and advanced fibrosis are those at greatest risk of developing hepatic complications and cardiovascular disease. There are still no available non-invasive methods that allow for correct diagnosis and staging of NAFLD. The implementation of Artificial Intelligence (AI) techniques based on artificial neural networks and deep learning systems (Deep Learning System) as a tool for medical diagnoses represents a bona fide technological revolution that introduces an innovative approach to improving health processes.

Conditions

  • Non-alcoholic Fatty Liver Disease (NAFLD)

Interventions

OTHER

This is an observational study.

This is an observational study. No intervention is planned outside of usual clinical practice.

Sponsors & Collaborators

  • Servicio Cántabro de Salud

    collaborator OTHER

  • Instituto de Investigación Marqués de Valdecilla

    lead OTHER

Eligibility

Min Age
19 Years
Max Age
74 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-09-30
Primary Completion
2020-09-30
Completion
2020-12-31

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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 NCT04099147 on ClinicalTrials.gov