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To Evaluate the Use of Radiomics to Classify Between Idiopathic Pulmonary Fibrosis and Interstitial Lung Disease

NCT04430491 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 300

Last updated 2020-06-12

No results posted yet for this study

Summary

To investigate the ability of machine learning models based on radiomic features extracted from thin-section CT images to differentiate IPF patients from non-IPF interstitial lung diseases.

Conditions

Interventions

DIAGNOSTIC_TEST

radiomics

The high-throughput extraction of large amounts of quantitative image features from medical images

Sponsors & Collaborators

  • Université Libre de Bruxelles

    collaborator OTHER

  • Maastricht University

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2005-01-01
Primary Completion
2017-01-01
Completion
2017-07-01

Countries

  • Netherlands

Study Locations

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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 NCT04430491 on ClinicalTrials.gov