A fuzzy clustering-based approach for classifying covid-19 patients by age and early symptom indicators | [Lahore Garrison University Research Journal of Computer Science and Information Technology • 2023]

Author(s):

1. Haris Ahmed: College of Computing and Information Sciences, Karachi Institute of Economics and Technology, Karachi, Pakistan.

2. Muhammad Affan Alim: College of Computing and Information Sciences, Karachi Institute of Economics and Technology, Karachi, Pakistan.

3. Waleej Haider: Department of Computer Science & Information Technology, Sir Syed University of Engineering and Technology, Karachi, Pakistan

4. Muhammad Nadeem: Department of Computer Science & Information Technology, Sir Syed University of Engineering and Technology, Karachi, Pakistan

5. Ahsan Masroor: College of Computing and Information Sciences, Karachi Institute of Economics and Technology, Karachi, Pakistan.

Abstract:

COVID-19, a devastating illness affecting people worldwide, poses challenges in determining the severity of the patient's condition during the early stages of infection. To address this issue, we propose a fuzzy clustering-based model that accurately classifies COVID-19 patients based on age and the severity of early symptoms (fever, dry cough, breathing difficulties, headache, smell, and taste disturbance). This model aims to enable prompt and personalized therapy for diagnosed patients. Compared to previous hard clustering tactics, our method shows promising results in reducing COVID-19-related deaths and increasing the likelihood of full recovery for affected individuals.

Page(s): 29-37

DOI: 10.54692/lgurjcsit.2023.0702410

Published: Journal: Lahore Garrison University Research Journal of Computer Science and Information Technology, Volume: 7, Issue: 2, Year: 2023

Keywords:

Coronaviruses , Disease , Classification , Fuzzy Clustering , Fuzzy C Means

References:

References are not available for this document.

Citations

Citations are not available for this document.

Citations

Downloads

Views