Convolutional neural network model based on radiological images to support COVID-19 diagnosis: Evaluating database biases.

ABSTRACT: As SARS-CoV-2 has spread quickly throughout the world, the scientific community has spent major efforts on better understanding the characteristics of the virus and possible means to prevent, diagnose, and treat COVID-19. A valid approach presented in the literature is to develop an image-based method to support COVID-19 diagnosis using convolutional neural networks (CNN). Because the availability of radiological data is rather limited due to the novelty of COVID-19, several methodologies consider reduced datasets, which may be inadequate, biasing the model. Here, we performed an analysis combining six different databases using chest X-ray images from open datasets to distinguish images of infected patients while differentiating COVID-19 and pneumonia from 'no-findings' images. In addition

SUBMITTER: Maior CBS 

PROVIDER: S-EPMC7920391 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature