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)

Starting a Jupyter session

Next, we will start a Jupyter session so that we can import our data into Python and make a machine learning model. A detailed example of creating a new Jupyter Notebook was presented in Chapter 1, Introduction to Healthcare Analytics. Here are the steps:

  1. Locate the Jupyter application on your computer and start it.
  2. In the new Jupyter tab that was opened in your default browser, navigate to the directory where you wish to save the notebook.
  3. Locate the New drop-down menu on the upper right of the console, click it, and select Python 3.
  4. You should see a new notebook, named Untitled.
  5. To rename your notebook, click on the name of the notebook in the upper left. A cursor should appear. Type in the desired name. We have named our notebook ED_predict.

You are now ready to import the dataset into Jupyter.