Abstract: Advances in technology have a swift impact on any area of life, whether medical or other. Through its analysis of data, artificial intelligence has shown promising results for health care. Over 100 countries have been affected by COVID-19 in no time. People worldwide are vulnerable in the future to its impacts. A control system for the detection of corona virus is imperative. The detection of disease using different AI methods may be one solution to manage the current catastrophe. This article classified textual clinical reports by using classical and ensemble machine algorithms into four classes. The study has used the concept of Natural language processing in which reports are classified using machine learning. In this work we have performed the classification using Naïve Bayes, Support Vector Machine, Logistic regression and Decision tree and we have observed decision tree has outperformed other state of algorithms with an accuracy of 97.8%. Before implementing the classification, feature engineering has also applied.
Keywords: Coronavirus, Naïve Bayes, Artificial Intelligence, Natural Language Processing, Precision.
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DOI:
10.17148/IJARCCE.2020.91105
