Trials / Withdrawn
WithdrawnNCT04418245
CT Biomarkers Identification by Artificial Intelligence for COVID-19 Prognosis
Identification of Thoracic CT Scan Biomarkers by Deep Learning for Evaluating the Prognosis of Patients With COVID-19 Disease
- Status
- Withdrawn
- Phase
- —
- Study type
- Observational
- Enrollment
- 0 (actual)
- Sponsor
- Centre Hospitalier Universitaire de Nīmes · Academic / Other
- Sex
- All
- Age
- —
- Healthy volunteers
- Not accepted
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
| Type | Name | Description |
|---|---|---|
| DIAGNOSTIC_TEST | Imaging by thoracic scanner | Low-dose computed tomography |
Timeline
- Start date
- 2020-03-01
- Primary completion
- 2021-09-01
- Completion
- 2021-09-01
- First posted
- 2020-06-05
- Last updated
- 2025-03-10
Locations
6 sites across 2 countries: France, Martinique
Source: ClinicalTrials.gov record NCT04418245. Inclusion in this directory is not an endorsement.