This is the code repository for Healthcare Analytics Made Simple, published by Packt.
Techniques in healthcare computing using machine learning and Python
In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists’ work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes.
This book covers the following exciting features:
- Gain valuable insight into healthcare incentives, finances, and legislation
- Discover the connection between machine learning and healthcare processes
- Use SQL and Python to analyze data
- Measure healthcare quality and provider performance
- Identify features and attributes to build successful healthcare models
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
string_1 = '1'
string_2 = '2'
string_sum = string_1 + string_2
print(string_sum)
Following is what you need for this book: Healthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.
With the following software and hardware list you can run all code files present in the book (Chapter 1-9).
| Chapter | Software required | OS required |
|---|---|---|
| 1 | Anaconda: 4.4.0 | 6GB of RAM, i5 Pentium, Windows 10 OS |
| 4 | Python: 3.6.1 | 6GB of RAM, i5 Pentium, Windows 10 OS |
| 5 | NumPy: 1.12.1 | 6GB of RAM, i5 Pentium, Windows 10 OS |
| 6 | pandas: 0.20.1 | 6GB of RAM, i5 Pentium, Windows 10 OS |
| 7 | scikit-learn: 0.18.1,matplotlib: 2.0.2 | 6GB of RAM, i5 Pentium, Windows 10 OS |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
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.
Click here if you have any feedback or suggestions.
If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.