Kernel-Based Machine Learning Techniques: An Innovative Way of Designing Healthcare Systems and Services

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Author(s): Kumar Vijay (Manav Rachna International University, India), Saxena Arti (Manav Rachna International University, India)and Kumar Suresh (Manav Rachna International University, India)
Copyright: 2018
Pages: 24
Source title: Big Data Management and the Internet of Things for Improved Health Systems
Source Author(s)/Editor(s): Brojo Kishore Mishra (C. V. Raman College of Engineering, India)and Raghvendra Kumar (LNCT Group of Colleges, India)
DOI: 10.4018/978-1-5225-5222-2.ch015

Keywords: Computer Science & IT / Health Information Systems / Internet Technologies / Medical Information Science Reference

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Abstract

Health care is considered as the fundamental right of every citizen and it is principle duty of every country to provide good health care facilities. Many developed countries spend substantial amount of gross domestic product (GDP) on healthcare. In this chapter, we discuss kernel based machine learning techniques, i.e., k-PCA (Kernel principal component analysis) and its related properties with a aim to prescribe cost effective treatments and easy diagnosis of diseases. This objective could be met only by the serious collaboration between physician and data scientist. We discussed that how we could construct a kernel and exact features based on the given dataset. Also, we compared the proposed method with the other methods. For the sake of easy understanding, applications of the proposed method are included in the text.

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Kernel-Based Machine Learning Techniques: An Innovative Way of Designing Healthcare Systems and Services

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