Analysis of identifying COVID-19 with deep learning model

ABSTRACT

Coronary Virus Disease 2019 swept the world and caused serious impact on human society. Doctors usually use CT scan pictures and chest X-ray images to determine whether a patient is infected. Many researchers try to use deep learning methods to test COVID-19 of patients. However, there are many problems when using deep learning methods for feature extraction, such as fewer data samples, unclear pictures, and pictures containing special marks. This article uses deep learning methods for COVID-19 detection and visual analysis of popular deep learning methods. Experiments verify that when using deep learning in the public small sample COVID-19 dataset, a small part of the test results are not reliable. We propose solutions to the problems of deep learning during COVID-19 detection. © 2020 Institute of Physics Publishing. All rights reserved.