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Machine Learning-Based Approach for Predictive Analytics in Healthcare
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Author(s): Sandeep Kumar Hegde (NMAM Institute of Technology, India)and Monica R. Mundada (M.S. Ramaiah Institute of Technology, India)
Copyright: 2022
Pages: 25
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.ch010
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Abstract
In this internet era, due to digitization in every application, a huge amount of data is produced digitally from the healthcare sectors. As per the World Health Organization (WHO), the mortality rate due to the various chronic diseases is increasing each day. Every year these diseases are taking lives of at least 50 million people globally, which includes even premature deaths. These days, machine learning (ML)-based predictive analytics are turning out as effective tools in the healthcare sectors. These techniques can extract meaningful insights from the medical data to analyze the future trend. By predicting the risk of diseases at the preliminary stage, the mortality rate can be reduced, and at the same time, the expensive healthcare cost can be eliminated. The chapter aims to briefly provide the domain knowledge on chronic diseases, the biological correlation between theses disease, and more importantly, to explain the application of ML algorithm-based predictive analytics in the healthcare sectors for the early prediction of chronic diseases.
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