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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 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

Programming in Python – an illustrative example

In the previous sections, we discussed variable types and data containers. There are many more aspects of Python programming, such as control flow with if/else statements, loops, and comprehensions; functions; and classes and object-oriented programming. Commonly, Python programs are packaged into modules, which are self-standing scripts that can be run from the command line to perform computing tasks.

Let's introduce some of these concepts in Python with a "module" of our own (you can use the Jupyter Notebook for this):

from math import pow


LB_TO_KG = 0.453592
IN_TO_M = 0.0254


class Patient:
def __init__(self, name, weight_lbs, height_in):
self.name = name
self.weight_lbs = weight_lbs
self.weight_kg = weight_lbs * LB_TO_KG
self.height_in = height_in
self.height_m = height_in...
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