Disease Prediction using Machine Learning, Deep Learning and Data Analytics

Author(s): Kanika Soni, Shelly Sachdeva and Shivani Batra * .

DOI: 10.2174/9789815179125124010016

Role of Database in Epidemiological Situation

Pp: 159-171 (13)

Buy Chapters
  • * (Excluding Mailing and Handling)

Disease Prediction using Machine Learning, Deep Learning and Data Analytics

Role of Database in Epidemiological Situation

Author(s): Kanika Soni, Shelly Sachdeva and Shivani Batra * .

Pp: 159-171 (13)

DOI: 10.2174/9789815179125124010016

* (Excluding Mailing and Handling)

Abstract

In this technological era, the technology of databases is very essential to many aspects of modern life. To give the prospective medical practitioner, the finest in class and most recent medical knowledge, it seems mandatory that education in the health domain be well-integrated with the most recent databases. This is because there is a growing demand for it and there are benefits from the collaboration of healthrelated issues of the public and database technology. Database technology can help improve health in several ways, including connecting geographically separated health providers and patients, collecting data for research studies like drug and vaccine trials, keeping track of chronic diseases, and guaranteeing that patients follow their prescribed treatments. In this pandemic situation of COVID-19, which the whole world is currently suffering, the current paper attempts to emphasize the databases’ role. It illustrates how the COVID-19 Dataset can be stored, queried, and analyzed, and helps in providing decision support to various end-users. We have performed descriptive analysis by executing specific queries on the COVID-19 Dataset. Then, we performed predictive analysis using two data analysis techniques on the COVID-19 Dataset to approximate the situation in some major cities of India. Further, we have visualized our results to get valuable information from our analysis.