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Machine Learning-Based Categorization of COVID-19 Patients

Machine Learning-Based Categorization of COVID-19 Patients

Tanvi Arora (CGC College of Engineering, India)
Copyright: © 2022 |Pages: 20
DOI: 10.4018/978-1-7998-9012-6.ch010
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Abstract

The world has been put to a standstill by the COVID-19 pandemic, which has been caused by the SARS-CoV-2 (initially called 2019-nCoV) infecting agent. Moreover, this pandemic is spreading like a wildfire. Even the developed nations are running short of hospital beds and ventilators to treat the critically ill. Considering the total population of the world and the pace at which this pandemic is spreading, it not possible to hospitalize all the positive patients with intensive care facilities. In the chapter, the authors present a machine learning-based approach that will categorize the COVID-19 positive patients into five different categories, namely asymptomatic, mild, moderate, severe, and critical. The proposed system is capable of classifying the COVID-19-affected patients into five distinct categories using selected features of age, gender, ALT, hemoglobin, WBC, heart disease, hypertension, fever, muscle ache, shortness of breath with 97.5% accuracy.
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Literature Review

The COVID 19 pandemic has emerged just a couple of months ago, and the researchers have put in much effort to study the characteristics of the widespread disease. Although much work in the domain of machine learning has not yet been carried out in this work. But the researchers have tried to detect the presence of the COVID 19 pandemic by evaluating the Chest X-ray images(WANG, 2020) or the CT images of the chest(Ai et al., 2020)(Bai et al., 2020)(Pan et al., 2020)(Shen et al., 2020) using the features of the images of the lungs captured.

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