Open Access iconOpen Access

ARTICLE

crossmark

Intelligent Decision Support System for COVID-19 Empowered with Deep Learning

Shahan Yamin Siddiqui1,2, Sagheer Abbas1, Muhammad Adnan Khan3,*, Iftikhar Naseer4, Tehreem Masood4, Khalid Masood Khan3, Mohammed A. Al Ghamdi5, Sultan H. Almotiri5

1 School of Computer Science, NCBA&E, Lahore, 54000, Pakistan
2 School of Computer Science, Minhaj University Lahore, Lahore, 54000, Pakistan
3 Department of Computer Science, Lahore Garrison University, Lahore, 54792, Pakistan
4 Department of Computer Science & Information Technology, Superior University, Lahore, 54000, Pakistan
5 Computer Science Department, Umm Al-Qura University, Makkah City, 715, Saudi Arabia

* Corresponding Author: Muhammad Adnan Khan. Email: email

(This article belongs to the Special Issue: Machine Learning and Computational Methods for COVID-19 Disease Detection and Prediction)

Computers, Materials & Continua 2021, 66(2), 1719-1732. https://doi.org/10.32604/cmc.2020.012585

Abstract

The prompt spread of Coronavirus (COVID-19) subsequently adorns a big threat to the people around the globe. The evolving and the perpetually diagnosis of coronavirus has become a critical challenge for the healthcare sector. Drastically increase of COVID-19 has rendered the necessity to detect the people who are more likely to get infected. Lately, the testing kits for COVID-19 are not available to deal it with required proficiency, along with-it countries have been widely hit by the COVID-19 disruption. To keep in view the need of hour asks for an automatic diagnosis system for early detection of COVID-19. It would be a feather in the cap if the early diagnosis of COVID-19 could reveal that how it has been affecting the masses immensely. According to the apparent clinical research, it has unleashed that most of the COVID-19 cases are more likely to fall for a lung infection. The abrupt changes do require a solution so the technology is out there to pace up, Chest X-ray and Computer tomography (CT) scan images could significantly identify the preliminaries of COVID-19 like lungs infection. CT scan and X-ray images could flourish the cause of detecting at an early stage and it has proved to be helpful to radiologists and the medical practitioners. The unbearable circumstances compel us to flatten the curve of the sufferers so a need to develop is obvious, a quick and highly responsive automatic system based on Artificial Intelligence (AI) is always there to aid against the masses to be prone to COVID-19. The proposed Intelligent decision support system for COVID-19 empowered with deep learning (ID2S-COVID19-DL) study suggests Deep learning (DL) based Convolutional neural network (CNN) approaches for effective and accurate detection to the maximum extent it could be, detection of coronavirus is assisted by using X-ray and CT-scan images. The primary experimental results here have depicted the maximum accuracy for training and is around 98.11 percent and for validation it comes out to be approximately 95.5 percent while statistical parameters like sensitivity and specificity for training is 98.03 percent and 98.20 percent respectively, and for validation 94.38 percent and 97.06 percent respectively. The suggested Deep Learning-based CNN model unleashed here opts for a comparable performance with medical experts and it is helpful to enhance the working productivity of radiologists. It could take the curve down with the downright contribution of radiologists, rapid detection of COVID-19, and to overcome this current pandemic with the proven efficacy.

Keywords


Cite This Article

APA Style
Siddiqui, S.Y., Abbas, S., Khan, M.A., Naseer, I., Masood, T. et al. (2021). Intelligent decision support system for COVID-19 empowered with deep learning. Computers, Materials & Continua, 66(2), 1719-1732. https://doi.org/10.32604/cmc.2020.012585
Vancouver Style
Siddiqui SY, Abbas S, Khan MA, Naseer I, Masood T, Khan KM, et al. Intelligent decision support system for COVID-19 empowered with deep learning. Comput Mater Contin. 2021;66(2):1719-1732 https://doi.org/10.32604/cmc.2020.012585
IEEE Style
S.Y. Siddiqui et al., “Intelligent Decision Support System for COVID-19 Empowered with Deep Learning,” Comput. Mater. Contin., vol. 66, no. 2, pp. 1719-1732, 2021. https://doi.org/10.32604/cmc.2020.012585

Citations




cc Copyright © 2021 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 4114

    View

  • 1884

    Download

  • 0

    Like

Share Link