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

NCT04313946 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 200

Last updated 2020-04-27

No results posted yet for this study

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

Conditions

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

Interventions

DIAGNOSTIC_TEST

Scanning Chest X-rays and performing AI algorithms on images

Chest X-Rays; AI CNNs; Results

Sponsors & Collaborators

  • Falcon Trading Iasi

    collaborator UNKNOWN

  • Romanian Academy of Medical Sciences

    collaborator UNKNOWN

  • Professor Adrian Covic

    lead OTHER

Principal Investigators

  • Alexandru Burlacu, Lecturer · University of Medicine and Pharmacy Gr T Popa - Iasi

  • Radu Dabija, Lecturer · University of Medicine and Pharmacy Gr T Popa - Iasi

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-03-18
Primary Completion
2020-08-16
Completion
2020-08-18

Countries

  • Italy
  • Romania
  • United Kingdom

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 NCT04313946 on ClinicalTrials.gov