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)

Data structures and containers

In the last section, we talked about variable types that store single values. Now we will move on to data structures that can hold multiple values. These data structures are lists, tuples, dictionaries, and sets. Lists and tuples are commonly referred to as sequences in Python. In this book, we will use the terms data structures and data containers interchangeably.

Lists

Lists are a widely used data structure that can hold multiple values. Let's look at some features of lists:

  • To make a list, we use square brackets, [].
    Example: my_list = [1, 2, 3].
  • Lists can hold any combination of numeric types, strings, Boolean types, tuples, dictionaries, or even other lists.
    Example: my_diverse_list...