So far in this book, we've examined the exciting history of healthcare analytics and some of the ways it currently impacts our healthcare system. In this chapter, we provide a sense of the latest developments in the field and what will likely be coming to healthcare analytics in the not-so-distant future. We'll delve into healthcare and the internet, specifically the Internet of Things (IoT) and social media applications, to see how they are playing roles in improving health. Next, we'll take a look at some of the new algorithms (collectively referred to as "deep learning") that are achieving state-of-the-art performance in medical prediction tasks. Finally, although this book has presented the state of healthcare analytics in a hopeful and optimistic fashion, there are still some considerable obstacles...

Healthcare Analytics Made Simple
By :

Healthcare Analytics Made Simple
By:
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)
Preface
Introduction to Healthcare Analytics
Healthcare Foundations
Machine Learning Foundations
Computing Foundations – Databases
Computing Foundations – Introduction to Python
Measuring Healthcare Quality
Making Predictive Models in Healthcare
Healthcare Predictive Models – A Review
The Future – Healthcare and Emerging Technologies
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