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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 FREE CHAPTER 2. Healthcare Foundations 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

Case details – predicting mortality for a cardiology practice

The cardiology practice you are working with has two physicians on staff: Dr. Johnson and Dr. Wu. While the practice has many patients, they are interested in identifying which patients who visit are at high risk of all-cause mortality within the next 6 months. Having an outpatient visit sometime in 2016 makes up the inclusion criteria for the analytics. The target variable is whether the patient passed away within 6 months of their visit.

Now that we've reviewed the details of the modeling assignment, let's take a look at the five patients in the database. The preliminary data sent to you by the cardiology practice includes information on five patients, distributed across six tables. The following are case vignettes for each of the patients. Note that this section is heavy on clinical terminology related...

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