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Healthcare Analytics Made Simple

You're reading from   Healthcare Analytics Made Simple Techniques in healthcare computing using machine learning and Python

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Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781787286702
Length 268 pages
Edition 1st Edition
Languages
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Authors (2):
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Vikas (Vik) Kumar Vikas (Vik) Kumar
Author Profile Icon Vikas (Vik) Kumar
Vikas (Vik) Kumar
Shameer Khader Shameer Khader
Author Profile Icon Shameer Khader
Shameer Khader
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Table of Contents (11) Chapters Close

Preface 1. Introduction to Healthcare Analytics 2. Healthcare Foundations FREE CHAPTER 3. Machine Learning Foundations 4. Computing Foundations – Databases 5. Computing Foundations – Introduction to Python 6. Measuring Healthcare Quality 7. Making Predictive Models in Healthcare 8. Healthcare Predictive Models – A Review 9. The Future – Healthcare and Emerging Technologies 10. Other Books You May Enjoy

Data engineering with SQL – an example case

For this chapter, let's pretend you secured a predictive analytics assignment with a cardiology practice located in the United States. The practice wants you to predict which patients are at risk of dying within 6 months of their visit to the clinic. They make their data available to you in the form of a database that includes six tables. For simplicity, we truncate the database to include the information for five patients only. Our task is to manipulate the data using the SQL language to consolidate it into a single table so that it can be used for machine learning. We will first go over the patients in the database and the database structure. Then, we will introduce basic SQL concepts for engineering and manipulate the data into a form amenable to machine learning.

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