Deep Fractional Max Pooling Neural Network for COVID-19 Recognition.

Shui-Hua Wang,Suresh Chandra Satapathy,Shi-Xin Chen,Donovan Anderson,Yu Dong Zhang

doi:10.3389/fpubh.2021.726144

Abstract

Aim: Coronavirus disease 2019 (COVID-19) is a form of disease triggered by a new strain of coronavirus. This paper proposes a novel model termed “deep fractional max pooling neural network (DFMPNN)” to diagnose COVID-19 more efficiently.Methods: This 12-layer DFMPNN replaces max pooling (MP) and average pooling (AP) in ordinary neural networks with the help of a novel pooling method called “fractional max-pooling” (FMP). In addition, multiple-way data augmentation (DA) is employed to reduce overfitting. Model averaging (MA) is used to reduce randomness.Results: We ran our algorithm on a four-category dataset that contained COVID-19, community-acquired pneumonia, secondary pulmonary tuberculosis (SPT), and healthy control (HC). The 10 runs on the test set show that the micro-averaged F1 (MAF) score of our DFMPNN is 95.88%.Discussions: This proposed DFMPNN is superior to 10 state-of-the-art models. Besides, FMP outperforms traditional MP, AP, and L2-norm pooling (L2P).

Highlights

Coronavirus disease 2019 (COVID-19) is a form of disease triggered by a new strain of coronavirus
To effectively diagnose COVID-19, there exist two types of methods: (i) polymerase chain reaction (PCR), real-time reverse-transcriptase PCR with nasopharyngeal swab samples to test the existence of RNA fragments [1]; and (ii) chest imaging (CI) examines the evidence of COVID-19 in the lung
The reverse-transcriptase PCR (rRT-PCR) is commonly used nowadays, but it has three shortcomings: (i) It has to wait for a few days to get the results; (ii) The samples are contaminated by the environment; (iii) Its performances on COVID-19 variants [2] are still under investigation

Summary

Introduction

Coronavirus disease 2019 (COVID-19) is a form of disease triggered by a new strain of coronavirus. To effectively diagnose COVID-19, there exist two types of methods: (i) polymerase chain reaction (PCR), real-time reverse-transcriptase PCR (rRT-PCR) with nasopharyngeal swab samples to test the existence of RNA fragments [1]; and (ii) chest imaging (CI) examines the evidence of COVID-19 in the lung.

Objectives

Results

Conclusion