Can you detect covid-19 using machine learning?

 



Technology advancements have a rapid effect on every field of life, be it medical field or any other field. Artificial intelligence has shown the promising results in health care through its decision making by analyzing the data. COVID-19 has affected more than 100 countries in a matter of no time. This will affect people all across the planet in the future.

The development of a control system that can detect the coronavirus is critical. The detection of disease with the use of various AI tools could be one option to control the current chaos. Using classical and ensemble machine learning techniques, we categorized textual clinical reports into four types in this research.

Feature engineering was performed using techniques like Term frequency/inverse document frequency (TF/IDF), Bag of words (BOW) and report length. Traditional and ensemble machine learning classifiers were given these features. Logistic regression and Multinomial Naïve Bayes showed better results than other ML algorithms by having 96.2% testing accuracy. In future recurrent neural network can be used for better accuracy.

Variants of Covid-19:

Country/region

Scientific name

WHO name

Kent, UK

B.1.1.7

Alpha

South Africa

B.1.351

Beta

Brazil

P.1

Gamma

India

B.1.617.2

Delta

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