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Predictive Analytics for Healthcare

Predictive Analytics for Healthcare
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Author(s): Pushpalatha M. N. (Ramaiah Institute of Technology, India), Parkavi A. (M.S. Ramaiah Institute of Technology, India) and Sini Anna Alex (M.S. Ramaiah Institute of Technology, India)
Copyright: 2022
Pages: 23
Source title: Deep Learning Applications for Cyber-Physical Systems
Source Author(s)/Editor(s): Monica R. Mundada (M.S. Ramaiah Institute of Technology, India), S. Seema (M.S. Ramaiah Institute of Technology, India), Srinivasa K.G. (National Institute of Technical Teachers Training and Research, Chandigarh, India) and M. Shilpa (M.S. Ramaiah Institute of Technology, India)
DOI: 10.4018/978-1-7998-8161-2.ch012

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Abstract

The healthcare scheme in India has a lot of differences between rural and urban areas in terms of quality along with changes in private and public healthcare systems. The healthcare system is massive in India and full of inconsistencies and complexities like the other countries. Predictive analytics will help to improve the healthcare systems by providing valuable insight in healthcare. A huge amount of different data sets is generated because of the digitization of healthcare. This digitization allows us to use predictive analytics for better patient outcomes. Predictive analytics is utilized in decision-making activities and prediction making about the future events which are unknown. In this chapter, a brief overview of the Indian healthcare systems is given, along with data representations, challenges, issues, and risks associated with applying predictive analytics in healthcare and case studies with respect to regression and classification models.

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