Book Image

Healthcare Analytics Made Simple

By : Vikas (Vik) Kumar, Shameer Khader
Book Image

Healthcare Analytics Made Simple

By: Vikas (Vik) Kumar, Shameer 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)

Introduction to scikit-learn

Entire books have been written on scikit-learn (http://scikit-learn.org/stable/). The scikit-learn library has numerous submodules. Only a few of these submodules will be used in this book (in Chapter 7, Making Predictive Models in Healthcare). These include the sklearn.linear_model and sklearn.ensemble submodules, for example. Here we will give an overview of some of the more commonly used submodules. For convenience, we have grouped the relevant modules into various segments of the data science pipeline discussed in Chapter 1, Introduction to Healthcare Analytics.

Sample data

scikit-learn includes several sample datasets in the sklearn.datasets submodule. At least two of these datasets, sklearn...