Title: Artificial intelligence methods for image classification applied to biological sounds for the early diagnosis of cardiorespiratory pathologies and COVID-19 infection

Authors: Agostino Giorgio

Addresses: DEI (Electrical and Information Department) – Politecnico di Bari, Via E. Orabona, 4, 70125, Bari, Italy

Abstract: With the spread of the COVID-19 pandemic, the scientific community took prompt action to seek adequate solutions for the prevention and treatment of the disease. However, what seems less developed at present are methods for early diagnosis of the disease which would be useful especially when it is becoming more complicated towards interstitial pneumonia which is the main cause of ICU admissions and deaths. The aim of this work is to describe methods typically used for signal and image digital processing, especially artificial intelligence (AI) algorithms, which could allow a very early diagnosis of the onset of COVID-19 infection as well as many other respiratory and cardiac pathologies. For this purpose, at least for a first screening, the use of medium-capacity smartphones may also be sufficient, without the need to resort to expensive medical equipment and diagnostic tests that require long waiting times and are always onerous.

Keywords: COVID-19; artificial intelligence; AI; digital signal processing; MATLAB; digital medical devices; biological sounds auscultation.

DOI: 10.1504/IJBET.2023.132547

International Journal of Biomedical Engineering and Technology, 2023 Vol.42 No.3, pp.281 - 316

Received: 01 Jul 2021
Accepted: 24 Sep 2021
Published online: 28 Jul 2023 *

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