Trials / Completed
CompletedNCT04347369
A Retrospective Study of Neural Network Model to Dynamically Quantificate the Severity in COVID-19 Disease
a Retrospective Study of Neural Network Model to Dynamically Quantificate the Severity in COVID-19 Disease
- Status
- Completed
- Phase
- —
- Study type
- Observational
- Enrollment
- 1,000 (actual)
- Sponsor
- Xinqiao Hospital of Chongqing · Academic / Other
- Sex
- All
- Age
- 18 Years – 80 Years
- Healthy volunteers
- —
Summary
The research aim to collect large samples of COVID-19 disease patients with clinical symptoms, laboratory and imaging examination data. Screening the biological indicators which are related to the occurrence of severe diseases. Then, investigators using artificial intelligence (AI) technology deep learning method to find a prediction model that can dynamically quantify COVID-19 disease severity.
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| OTHER | other | clinical diagnosis |
Timeline
- Start date
- 2020-01-17
- Primary completion
- 2020-08-30
- Completion
- 2020-12-31
- First posted
- 2020-04-15
- Last updated
- 2024-02-23
Locations
1 site across 1 country: China
Source: ClinicalTrials.gov record NCT04347369. Inclusion in this directory is not an endorsement.