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)

Healthcare analytics and the internet

Physically, the internet is a specific computer network that connects millions of computing devices worldwide. Practically, it is an infrastructure that provides services to applications such as email, social networks, data storage, and communication (Kurose and Ross, 2013). The internet rose to prominence in the 1990s and affected virtually every industry in the global economy; healthcare is no exception. As we discussed in Chapter 2, Healthcare Foundations, clinical data is increasingly being stored electronically on computers, and third parties who perform analytics with this data often receive the data via the internet and use the cloud to store this data. Furthermore, the results of the analytics are often communicated back to the healthcare organization via an internet technology known as an application programming interface (API) by...