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CT Biomarkers Identification by Artificial Intelligence for COVID-19 Prognosis

NCT04418245 · Status: WITHDRAWN · Type: OBSERVATIONAL

Last updated 2025-03-10

No results posted yet for this study

Summary

The study hypothesis is that low-dose computed tomography (LDCT) coupled with artificial intelligence by deep learning would generate imaging biomarkers linked to the patient's short- and medium-term prognosis.

The purpose of this study is to rapidly make available an early decision-making tool (from the first hospital consultation of the patient with symptoms related to SARS-CoV-2) based on the integration of several biomarkers (clinical, biological, imaging by thoracic scanner) allowing both personalized medicine and better anticipation of the patient's evolution in terms of care organization.

Conditions

Interventions

DIAGNOSTIC_TEST

Imaging by thoracic scanner

Low-dose computed tomography

Sponsors & Collaborators

  • Centre Hospitalier Universitaire de Nīmes

    lead OTHER

Principal Investigators

  • Julien Frandon · CHU Nimes

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-03-01
Primary Completion
2021-09-30
Completion
2021-09-30

Countries

  • France
  • Martinique

Study Locations

More Related Trials

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 NCT04418245 on ClinicalTrials.gov