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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

Product type Paperback

Published in Jul 2018

Publisher Packt

ISBN-13 9781787286702

Length 268 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Data Analysis

Authors (2):

Kumar

Khader

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Table of Contents (17) Chapters

Title Page

Copyright and Credits

Packt Upsell

Foreword

Contributors

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

1. Other Books You May Enjoy

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Index

Additional analytics libraries

Here we mention three important packages that are frequently used for analytics: NumPy, SciPy, and matplotlib.

NumPy and SciPy

NumPy (www.numpy.org) is Python's matrix library. Using numpy.array() and similar constructs, large matrices can be created and various mathematical operations (including matrix addition and multiplication) can be performed on them. NumPy also has many functions for manipulating the shapes of matrices. Another feature of NumPy is the presence of familiar mathematical functions such as sin(), cos(), and exp().

SciPy (www.scipy.org) is a toolbox that contains many advanced mathematical modules. Its machine-learning-related subpackages include cluster, stats, sparse, and optimize. SciPy is an important package that enables scientific computing in Python.

matplotlib

matplotlib (https://matplotlib.org) is a popular Python 2-D plotting library. According to its website, one "can generate plots, histograms, power spectra, bar charts, error charts...

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Authors (2)

Kumar

Kumar

Dr. Vikas (Vik) Kumar grew up in the United States in Niskayuna, New York. He earned his MD from the University of Pittsburgh, but shortly afterwards he discovered his true calling of computers and data science. He then earned his MS in the College of Computing at Georgia Institute of Technology and has subsequently worked as a data scientist for both healthcare and non-healthcare companies. He currently lives in Atlanta, Georgia.

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Khader

Khader

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