Revealing the Effectiveness of Turmeric for COVID-19 through Analysis of Consumer’ Reviews Using Clustering, Text Mining and Deep Learning

Mehrbakhsh Nilashi, Rabab Ali Abumalloh

Abstract


Understanding COVID-19's nature along with clinical features will be essential in dealing with the outbreak of this virus. As the immune response of COVID-19 patients is found to be similar to the immune response of patients with MERS and SARS, those Complementary and Alternative Medicines (CAMs) are potential sources of bioactive compounds with antimicrobial activity can be beneficial in the prevention and treatment of COVID-19 virus infection. This paper investigates the role of curcumin, as an active component of the spice turmeric, in infectious diseases such as COVID-19. In addition, this paper provides some results from the WebMD data for the consumers’ satisfaction of turmeric consumption. The data analysis is performed using clustering, text mining and prediction techniques. The results show that the majority of consumers find turmeric as a useful CAM in improving their general health and well-being. Overall, the advantages of turmeric to infectious disease in the early stage of infection for prevention and treatment need additional evaluation. Nevertheless, because some clinical studies show turmeric effectiveness in infectious disease prevention and treatment, further clinical and consumer analysis should be conducted to reach robust conclusion on the benefit of turmeric beneficial for COVID-19 treatment. The outcome of this paper demonstrates the health benefits of turmeric and its effectiveness in immune system enhancement and protection against infectious diseases.


Keywords


Curcumin, Turmeric, COVID-19, Immune Response, Consumer Experience, Clustering, Text Mining

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Abstract

References


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