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 pandas

Almost all of the features we've discussed so far are features of base Python; that is, no external packages or libraries were required. The truth of the matter is that the majority of the code we write in this book will pertain to one of several external Python packages commonly used for analytics. The pandas library (http://pandas.pydata.org) is an integral part of the later programming chapters. The functions of pandas for machine learning are threefold:

  • Import data from flat files into your Python session
  • Wrangle, manipulate, format, and cleanse data using the pandas DataFrame and its library of functions
  • Export data from your Python session to flat files

Let's review each of these functions in turn.

Flat files are popular methods of storing healthcare-related data (along with HL7 formats, which are not covered in this book). A flat file...