Skip to main navigation Skip to search Skip to main content

A Survey of COVID-19 Detection From Chest X-Rays Using Deep Learning Methods

  • Vellore Institute of Technology
  • Noroff University College
  • Lebanese American University

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The coronavirus (COVID-19) outbreak has opened an alarming situation for the whole world and has been marked as one of the most severe and acute medical conditions in the last hundred years. Various medical imaging modalities including computer tomography (CT) and chest x-rays are employed for diagnosis. This paper presents an overview of the recently developed COVID-19 detection systems from chest x-ray images using deep learning approaches. This review explores and analyses the data sets, feature engineering techniques, image pre-processing methods, and experimental results of various works carried out in the literature. It also highlights the transfer learning techniques and different performance metrics used by researchers in this field. This information is helpful to point out the future research direction in the domain of automatic diagnosis of COVID-19 using deep learning techniques.

Original languageEnglish
JournalInternational Journal of Data Warehousing and Mining
Volume18
Issue number1
DOIs
StatePublished - 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • COVID-19 Detection
  • Chest X-Rays
  • Deep Learning
  • Survey
  • Transfer Learning

Fingerprint

Dive into the research topics of 'A Survey of COVID-19 Detection From Chest X-Rays Using Deep Learning Methods'. Together they form a unique fingerprint.

Cite this