An evolutionary ensemble learning for diagnosing COVID-19 via cough signals.

ABSTRACT: Objective The spread of the COVID-19 disease has caused great concern around the world and detecting the positive cases is crucial in curbing the pandemic. One of the symptoms of the disease is the dry cough it causes. It has previously been shown that cough signals can be used to identify a variety of diseases including tuberculosis, asthma, etc. In this paper, we proposed an algorithm to diagnose via cough signals the COVID-19 disease. Methods The proposed algorithm is an ensemble scheme that consists of a number of base learners, where each base learner uses a different feature extractor method, including statistical approaches and convolutional neural networks (CNN) for automatic feature extraction. Features are extracted from the raw signal and some transforms performed it, including

SUBMITTER: Najaran MHT 

PROVIDER: S-EPMC9882956 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature