Machine learning for coronavirus covid-19 detection from chest x-rays | Zendy

Luca Brunese | Zendy; Fabio Martinelli | Zendy; Francesco Mercaldo | Zendy; Antonella Santone | Zendy

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Machine learning for coronavirus covid-19 detection from chest x-rays

Author(s) -

Luca Brunese,

Fabio Martinelli,

Francesco Mercaldo,

Antonella Santone

Publication year - 2020

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2020.09.258

Subject(s) - covid-19 , computer science , exploit , artificial intelligence , coronavirus , set (abstract data type) , data set , machine learning , disease , virology , infectious disease (medical specialty) , medicine , computer security , pathology , outbreak , programming language

At the end of 2019, a new form of Coronavirus, called COVID-19, has widely spread in the world. To quickly screen patients with the aim to detect this new form of pulmonary disease, in this paper we propose a method aimed to automatically detect the COVID-19 disease by analysing medical images. We exploit supervised machine learning techniques building a model considering a data-set freely available for research purposes of 85 chest X-rays. The experiment shows the effectiveness of the proposed method in the discrimination between the COVID-19 disease and other pulmonary diseases.

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