Biomedical Letters

Research article | https://doi.org/10.47262/BL/10.1.20240301

An approach for detecting the severity levels of COVID-19 and associated features in district Gujranwala, Pakistan

Zameel Saleem 1, Shoaib Waris 1*, Asim Ali 3, Ameer Hamza 2, Muhammad Usman 2, Pervez Anwar 1, Tassaduq Hussain 4

1Department of Biological Sciences, University of Sialkot, Sialkot, P.O. Box 51340, Pakistan

2Department of Biochemistry, university of Sialkot, Sialkot, P.O. Box 51340, Pakistan

3Department of Pathology, University of Veterinary and Animal Sciences (UVAS), Lahore, Pakistan

4Department of Computer Sciences and IT, University of Sialkot, Sialkot, P.O. Box 51340, Pakistan

Abstract

COVID-19, a pandemic, attacked millions of people's health and economies across the world, particularly in low-income developing countries such as Pakistan. The study aims to develop a novel method and approach to diagnose COVID-19. Clinical features C-reactive protein, ferritin, and D-dimer levels were accessed to check the severity of COVID-19 positive patients. 160 patients were included in this study who had positive signs for COVID-19. Sandwich immune-detection and real time-PCR analyses were performed to access the clinical features of COVID-19. The results of clinical features and real time-PCR assay were compared using Artificial Intelligence (AI). Four classifiers; Support vector machine, Random Forest, K- nearest neighbor, and Neural network, were used to predict the results and the accuracy from these algorithms was 78.6%, 75.4%, 75.4%, and 63.9% respectively. The higher accuracy was from the Support vector Machine which shows 78.6% accuracy of clinical features results obtained from COVID-19 positive patients. In conclusion, this study provides an alternative diagnostic method for COVID-19 patients. Additionally, this study not only provided the diagnostic method but also evaluate severity of clinical features and also the cost-effective diagnosis of COVID-19 detection. The alternative way provided by this this study will be very helpful for the diagnosis of COVID-19 through basic test parameters.