Clinical Trials Directory

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UnknownNCT04313946

Artificial Intelligence Algorithms for Discriminating Between COVID-19 and Influenza Pneumonitis Using Chest X-Rays

The Benefits of Artificial Intelligence Algorithms (CNNs) for Discriminating Between COVID-19 and Influenza Pneumonitis in an Emergency Department Using Chest X-Ray Examinations

Status
Unknown
Phase
Study type
Observational
Enrollment
200 (estimated)
Sponsor
Professor Adrian Covic · Academic / Other
Sex
All
Age
Healthy volunteers
Not accepted

Summary

This project aims to use artificial intelligence (image discrimination) algorithms, specifically convolutional neural networks (CNNs) for scanning chest radiographs in the emergency department (triage) in patients with suspected respiratory symptoms (fever, cough, myalgia) of coronavirus infection COVID 19. The objective is to create and validate a software solution that discriminates on the basis of the chest x-ray between Covid-19 pneumonitis and influenza

Detailed description

This project aims to use artificial intelligence (image discrimination) algorithms; * specifically convolutional neural networks (CNNs) for scanning chest radiographs in the emergency department (triage) in patients with suspected respiratory symptoms (fever, cough, myalgia) of coronavirus infection COVID 19; * the objective is to create and validate a software solution that discriminates on the basis of the chest x-ray between Covid-19 pneumonitis and influenza; * this software will be trained by introducing X-Rays from patients with/without COVID-19 pneumonitis and/or flu pneumonitis; * the same AI algorithm will run on future X-Ray scans for predicting possible COVID-19 pneumonitis

Conditions

Interventions

TypeNameDescription
DIAGNOSTIC_TESTScanning Chest X-rays and performing AI algorithms on imagesChest X-Rays; AI CNNs; Results

Timeline

Start date
2020-03-18
Primary completion
2020-08-16
Completion
2020-08-18
First posted
2020-03-18
Last updated
2020-04-27

Locations

3 sites across 3 countries: Italy, Romania, United Kingdom

Source: ClinicalTrials.gov record NCT04313946. Inclusion in this directory is not an endorsement.