Application of Machine Learning for COVID-19 Data Analysis

Authors

  • Manisha Shinde-Pawar
  • Rajendra Pujari
  • Ayesha Mujawar
  • Alok Shah
  • Deepali Gala
  • Bhaskar Patil

DOI:

https://doi.org/10.47750/pnr.2022.13.03.053

Keywords:

COVID 19, Dominance Analysis, Fuzzy Logic, Machine Learning.

Abstract

The entire globe is facing the pandemic and it has devastated the life of society. On the grounds of diverse medical facilities and variants of COVID 19 cases the proposed solution provides in depth analysis of incidents generated information, which is information of COVID 19 patients which maximizes benefits to health organizations and also maximizes value relationship with its medical stakeholders. This gives rise a thirst for carrying out the study on the available data analysis of COVID 19 data and use of some machine learning techniques to support decision making by identifying patterns using fuzzy classifications, dominance analysis by using Principle component analysis and to provide machine learning based predictions on available data for COVID 19 cases specifically for severity level and level of recurrence with respect to different input parameters(Age, time of diagnosis, pre-existing conditions, and symptoms). So, the study focuses to identify relationships, patterns and dominance which will support COVID 19 medical research field.

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Published

2022-09-20

Issue

Section

Articles

How to Cite

Application of Machine Learning for COVID-19 Data Analysis. (2022). Journal of Pharmaceutical Negative Results, 13(3), 334-338. https://doi.org/10.47750/pnr.2022.13.03.053