Resumen

MEDJAHED, Seyyid Ahmed  y  OUALI, Mohammed. Automatic System for COVID-19 Diagnosis. Comp. y Sist. [online]. 2020, vol.24, n.3, pp.1131-1138.  Epub 09-Jun-2021. ISSN 2007-9737.  https://doi.org/10.13053/cys-24-3-3366.

During the last months, the virus COVID 19 spread globally, quickly and affected many people. This last, is an infection caused by severe acute respiratory. Unfortunately, the number of cases increases significantly and early diagnosis of this disease can help to save the health of patient and his entourage by stopping contamination. In this paper, we propose a process of COVID 19 diagnosis in Chest X-rays. This process is composed of three main steps. The first one is the feature extraction using four approaches. The second one is the feature selection phase using a new feature selection approach. The last phase is the classification. The classifier used in this approach is composed of four supervised classification approaches. The proposed work has been tested COVID-19 in X-ray images obtained by PyImageSearch.

Palabras llave : COVID-19 diagnosis; feature extraction; feature selection; classification; multi-verses optimizer.

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