An Advanced Machine Learning Model for Disease Prediction
Ayushi Sharma1, Shipra Shukla2

1Ayushi Sharma, CSE, Amity University, Noida, India.
2Dr. Shipra Shukla, Asst. Prof., CSE, Amity University, Noida, U.P., India. 

Manuscript received on May 25, 2020. | Revised Manuscript received on June 29, 2020. | Manuscript published on July 30, 2020. | PP: 1220-1225 | Volume-9 Issue-2, July 2020. | Retrieval Number: B4164079220/2020©BEIESP | DOI: 10.35940/ijrte.B4164.079220
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Abstract: To settle on right choices and pass on about vital control measures, numerous flare-up expectation models for anticipating COVID-19 are getting utilized all round the world. Straightforward conventional models have indicated extremely less precision rate for future forecast use, because of more significant levels of vulnerability and absence of proper information. Among the different machine learning model algorithms contemplated, an ensembled model was seen as giving the best outcomes. Because of the multifaceted nature of the virus’s temperament, this research paper recommends machine learning to be an extremely helpful gadget to consider in case of the ongoing pandemic. This paper gives a colossal benchmark to call attention to the probability of machine learning to be utilized as an instrument for future exploration on pandemic control and its timely prediction. Moreover, this paper delineates that the best prompts for pandemic prediction are frequently comprehended by combining machine learning, predictive analytics and visualisation tools like Tableau. The main purpose of this research is to build a perfect ML model prototype which can be later used when access to appropriate dataset (which is both large and consists of many different features) is available. Also, the secondary aim is to automate the process of reporting so as to facilitate quicker action by the concerned authorities, and help common people reach out to the correct destination for treatment or help. Furthermore, the Tableau analysis performed on the dataset is to provide more analytical depths for people with expertise in the medical domain. 
Keywords: COVID-19, machine learning, predictive analytics, Tableau.