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 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
Study Type
OBSERVATIONAL
Enrollment
200
Chest X-Rays; AI CNNs; Results
U.O. Multidisciplinare di Patologia Mammaria e Ricerca Traslazionale; Dipartimento Universitario Clinico di Scienze Mediche, Chirurgiche e della Salute Università degli Studi di Trieste
Cremona, Italy
RECRUITINGUniversity of Medicine and Pharmacy Gr T Popa
Iași, Romania
RECRUITINGDepartment of Cardiology at Chelsea and Westminster NHS hospital
London, United Kingdom
RECRUITINGCOVID-19 positive X-Rays
Number of participants with pneumonitis on Chest X-Ray and COVID 19 positive
Time frame: 6 months
COVID-19 negative X-Rays
Number of participants with pneumonitis on Chest X-Ray and COVID 19 negative
Time frame: 6 months
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