Automated medical diagnosis of COVID-19 through EfficientNet convolutional neural network.

ABSTRACT: COVID-19 infection was reported in December 2019 at Wuhan, China. This virus critically affects several countries such as the USA, Brazil, India and Italy. Numerous research units are working at their higher level of effort to develop novel methods to prevent and control this pandemic scenario. The main objective of this paper is to propose a medical decision support system using the implementation of a convolutional neural network (CNN). This CNN has been developed using EfficientNet architecture. To the best of the authors' knowledge, there is no similar study that proposes an automated method for COVID-19 diagnosis using EfficientNet. Therefore, the main contribution is to present the results of a CNN developed using EfficientNet and 10-fold stratified cross-validation. This paper prese

SUBMITTER: Marques G 

PROVIDER: S-EPMC7836808 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature