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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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Toc

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

Summary

In this chapter, we have built a predictive model for predicting outcomes in the emergency department. While there are many machine learning problems in healthcare, this exercise has demonstrated the issues typically faced as one preprocesses healthcare data, trains and scores models, and makes predictions with unlabeled data. This chapter marks the end of the coding portion of this book.

Now that we have seen the construction of a predictive model firsthand, the next logical question to ask is how predictive models have fared when compared with traditional statistical risk scores in predicting clinical outcomes. We explore that question in the next chapter.

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