On the Early Detection of COVID19 using Advanced Machine Learning Techniques: A Review

Mohammed Abdulazeem Siddiqui; Mohammed Akber Ali; Mohamed Deriche

doi:10.1109/SSD52085.2021.9429345

On the Early Detection of COVID19 using Advanced Machine Learning Techniques: A Review

Mohammed Abdulazeem Siddiqui, Mohammed Akber Ali, Mohamed Deriche

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

The outbreak of the new coronavirus (COVID19), has caused devastating effects and was declared as a major pandemic by the World Health Organization (WHO). Apart from knowing the main causes, it's very important to timely diagnose the virus in an individual, so that treatment and isolation (if needed) can start as early as possible and spread of the virus is contained among the healthy people. In this research, we discuss various machine learning (ML) and deep learning (DL) approaches that have been proposed for the diagnosis of the virus using different bio-indicators with particular focus on lungs imaging. A detailed analysis of existing techniques is presented with future perspective on the use of new machine learning techniques for the diagnosis of the COVID19 and other similar viruses.

Original language	English
Title of host publication	18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665414937
DOIs	https://doi.org/10.1109/SSD52085.2021.9429345
State	Published - 22 Mar 2021

Publication series

Name	18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

Automatic Detection
COVID19
CT Scan
Deep learning
ML
Ultrasound
Xray

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Signal Processing
Electrical and Electronic Engineering

UN SDGs

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

Access to Document

10.1109/SSD52085.2021.9429345

Cite this

Siddiqui, M. A., Ali, M. A., & Deriche, M. (2021). On the Early Detection of COVID19 using Advanced Machine Learning Techniques: A Review. In 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021 Article 9429345 (18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSD52085.2021.9429345

Siddiqui, Mohammed Abdulazeem ; Ali, Mohammed Akber ; Deriche, Mohamed. / On the Early Detection of COVID19 using Advanced Machine Learning Techniques : A Review. 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021).

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Siddiqui, MA, Ali, MA & Deriche, M 2021, On the Early Detection of COVID19 using Advanced Machine Learning Techniques: A Review. in 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021., 9429345, 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/SSD52085.2021.9429345

On the Early Detection of COVID19 using Advanced Machine Learning Techniques: A Review. / Siddiqui, Mohammed Abdulazeem; Ali, Mohammed Akber; Deriche, Mohamed.
18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021. Institute of Electrical and Electronics Engineers Inc., 2021. 9429345 (18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Siddiqui MA, Ali MA, Deriche M. On the Early Detection of COVID19 using Advanced Machine Learning Techniques: A Review. In 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021. Institute of Electrical and Electronics Engineers Inc. 2021. 9429345. (18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021). doi: 10.1109/SSD52085.2021.9429345

On the Early Detection of COVID19 using Advanced Machine Learning Techniques: A Review

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this