Medical Data Science And Processing Using Statistical Analysis In E-Healthcare For Covid-19
European Journal of Molecular & Clinical Medicine,
2022, Volume 9, Issue 8, Pages 1094-1118
AbstractData Science is one of the dominating fields in the today’s world. It plays its role in all the fields such as Agriculture, Healthcare, Education, Banking, and Entertainment. Data becomes the fuel of the Industry in 21st Century. This data is growing exponentially as the new data is getting generated from various sources such as YouTube, Face book, Mobile devices and Twitter in each and every millisecond of time. This data needs to be handled effectively which could not be done by the traditional data handling techniques/methods/tools. This invites many researchers to apply various data handling techniques using data science. E-healthcare system is considered as a digital healthcare system to perform disease prediction and analysis. Data Science techniques are predominantly adapted in E-healthcare system for the prediction of plenty of diseases such as various cancer prediction, heart diseases, autoimmune diseases, allergy and respiratory system diseases and so on. In addition to these disease prediction techniques, COVID’19 pandemic situation has made the researchers to make use of data science methods in E-healthcare systems. Hence, certain methods such as disease prevention and predictive medicine is useful in COVID-19 pandemic after performing pre-processing which involves huge volume of structured, unstructured and semi-structured data. Also, visual exploratory analysis technique using data science helps even the rural people to get the insight of understanding the COVID with respect to various symptoms, no. of COVID cases in each day, recovery rate & death rate and all the other details. This chapter discusses the impact of COVID-19 and its analysis using data science in E-healthcare system. Framework used for analysing the COVID-19 dataset using Software Engineering in connection with data science technique is also discussed. It provides a clear understanding of performing the disease prediction in a step-by-step manner. Results are shown using visual exploratory techniques.
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