Book Description: Health Analytics with R Learning Data Science Using Examples from Healthcare and Direct-to-Consumer Genetics provides an overview of health analytics using R programming language and data science techniques. The book covers topics such as data preprocessing, visualization, statistical modeling, machine learning, and deep learning, all within the context of healthcare and direct-to-consumer genetics. It also includes practical examples and case studies to illustrate how these concepts can be applied in real-world scenarios. The book begins by discussing the importance of health analytics and its relevance in today's healthcare system, followed by an introduction to R programming language and its applications in data analysis. The next section delves into data preprocessing, including data cleaning, transformation, and integration, as well as exploratory data analysis (EDA) techniques. This is followed by chapters on visualization, statistical modeling, machine learning, and deep learning, each of which builds upon the previous chapter to provide a comprehensive understanding of health analytics.

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