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Healthcare Analytics Made Simple

Healthcare Analytics Made Simple

By : Kumar, Khader
4.4 (8)
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Healthcare Analytics Made Simple

Healthcare Analytics Made Simple

4.4 (8)
By: Kumar, Khader

Overview of this book

In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists’ work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed. By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples.
Table of Contents (11 chapters)
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Summary

In this chapter, we have taken a look at some prominent value-based programs that are shaping the US healthcare industry today. We have seen how these programs quantify provider performance through the use of measures. Additionally, we have downloaded the data for comparing dialysis facilities and hospitals and worked through some code examples in Python to see how to analyze this data.

One might argue that the analysis in this chapter could be accomplished by using a spreadsheet application such as Microsoft Excel rather than programming. In Chapter 7, Making Predictive Models in Healthcare, we will train predictive models on a healthcare dataset to predict discharge status in the ED. As you will see, this type of analysis almost certainly requires writing code.

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