Vol.69, No.1, 2021, pp.21-34, doi:10.32604/cmc.2021.013453
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ARTICLE
Supervised Machine Learning-Based Prediction of COVID-19
  • Atta-ur-Rahman1, Kiran Sultan3, Iftikhar Naseer4, Rizwan Majeed5, Dhiaa Musleh1, Mohammed Abdul Salam Gollapalli2, Sghaier Chabani2, Nehad Ibrahim1, Shahan Yamin Siddiqui6,7, Muhammad Adnan Khan8,*
1 Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, 31441, Saudi Arabia
2 Department of Computer Information System, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, 31441, Saudi Arabia
3 Department of CIT, Faculty of Applied Studies, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
4 Department of Computer Science & Information Technology, Superior University, Lahore, 54000, Pakistan
5 Directorate of IT, The Islamia University of Bahawalpur, Bahawalpur, 63100, Pakistan
6 School of Computer Science, National College of Business Administration and Economics, Lahore, 54000, Pakistan
7 Department of Computer Science, Minhaj University Lahore, Lahore, 54000, Pakistan
8 Department of Computer Science, Faculty of Computing, Riphah International University Lahore Campus, Lahore, 54000, Pakistan
* Corresponding Author: Muhammad Adnan Khan. Email:
Received 30 August 2020; Accepted 06 December 2020; Issue published 04 June 2021
Abstract
COVID-19 turned out to be an infectious and life-threatening viral disease, and its swift and overwhelming spread has become one of the greatest challenges for the world. As yet, no satisfactory vaccine or medication has been developed that could guarantee its mitigation, though several efforts and trials are underway. Countries around the globe are striving to overcome the COVID-19 spread and while they are finding out ways for early detection and timely treatment. In this regard, healthcare experts, researchers and scientists have delved into the investigation of existing as well as new technologies. The situation demands development of a clinical decision support system to equip the medical staff ways to timely detect this disease. The state-of-the-art research in Artificial intelligence (AI), Machine learning (ML) and cloud computing have encouraged healthcare experts to find effective detection schemes. This study aims to provide a comprehensive review of the role of AI & ML in investigating prediction techniques for the COVID-19. A mathematical model has been formulated to analyze and detect its potential threat. The proposed model is a cloud-based smart detection algorithm using support vector machine (CSDC-SVM) with cross-fold validation testing. The experimental results have achieved an accuracy of 98.4% with 15-fold cross-validation strategy. The comparison with similar state-of-the-art methods reveals that the proposed CSDC-SVM model possesses better accuracy and efficiency.
Keywords
COVID-19; CSDC-SVM; artificial intelligence; machine learning; cloud computing; support vector machine
Cite This Article
. Atta-ur-Rahman, K. Sultan, I. Naseer, R. Majeed, D. Musleh et al., "Supervised machine learning-based prediction of covid-19," Computers, Materials & Continua, vol. 69, no.1, pp. 21–34, 2021.
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