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

Study Overview
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Brief Summary
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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
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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

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

Conditions
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COVID-19, Pneumonia, Viral, Influenza With Pneumonia, Flu Symptom, Flu Like Illness, Pneumonia, Interstitial, Pneumonia, Ventilator-Associated, Pneumonia Atypical

Intervention / Treatment
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* Diagnostic Test: Scanning Chest X-rays and performing AI algorithms on images


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: flu-like symptoms: myalgia, cough, fever, sputum Chest X-Rays COVID-19 biological tests Exclusion Criteria: patient refusal uncertain radiographs uncertain tests results
Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Symptomatic Patients<br>Our goal is to identify an artificial intelligence algorithm that can be run on lung radiographs in patients with influenza / respiratory viral symptoms who come to the emergency department / triage. This algorithm aims to identify the radiographs of patients with COVID-19 and those with influenza pneumonitis, with accuracy verified by COVID-19 tests. | Diagnostic Test: Scanning Chest X-rays and performing AI algorithms on images<br>* Chest X-Rays; AI CNNs; Results<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| COVID-19 positive X-Rays | Number of participants with pneumonitis on Chest X-Ray and COVID 19 positive | 6 months | 
| COVID-19 negative X-Rays | Number of participants with pneumonitis on Chest X-Ray and COVID 19 negative | 6 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Artificial Intelligence, CNNs, COVID-19, chest X-Ray, Emergency Department, Triage, Flu