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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

Importing the dataset

Before we load the dataset, there are some important facts about the data that must be acknowledged:

  • The data is in a fixed-width format, meaning that there is no delimiter. Column widths will have to be specified manually.
  • There is no header row that has column names.
  • If you were to open the data file using a text editor, you would see rows of data simply containing numbers.

Because column widths are necessary for importing .fwf files, we must import those first into our session. We have therefore made a helper .csv file, titled ED_metadata.csv, that contains the width, name, and variable type of each column. Our data only has 579 columns, so making such a file only took a couple of hours. If you have a bigger dataset, you may have to rely on automated width detection methods and/or more team members to do the grunt work of creating a schema for your data...

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