Healthcare Analytics Made Simple

Add a touch of data analysis to your healthcare systems and get amazing outcomes

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Healthcare Analytics Made Simple

Vikas “Vik” Kumar

Add a touch of data analysis to your healthcare systems and get amazing outcomes

Quick links: > What will you learn?> Table of content

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Book Details

ISBN 139781787286702
Paperback291 pages

Book Description

This book is a self-contained overview of machine learning for healthcare analytics. Book describes briefly the current international healthcare landscape, machine learning algorithms, and the Python programming language.Application of these principles to popular healthcare analytic use-cases that healthcare providers are clamoring to solve, such as readmission prediction and emergency department outcome evaluation etc. Each chapter will cover a new use-case with a new machine learning algorithm and will develop step-by-step code sufficient for implementation.

The functional outcomes of the book is to demonstrate that how Python packages are used for data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data, with the help of real-world examples.

Table of Contents

Chapter 1: Introduction to Healthcare, Machine Learning, and Software Development
Healthcare delivery in the U.S.
Global healthcare trends
Introduction to patient data
The healthcare machine learning pipeline
Privacy in healthcare
References and further reading
Summary
Chapter 2: Use Cases for Healthcare Machine Learning Apps
Machine learning in healthcare - infinite possibilities
U.S. Government-subsidized use cases
Current machine learning progress for leading causes of mortality
References and further reading
Summary
Chapter 3: Programming Foundations - Introduction to SQL
Introduction
References and Further Reading
Summary
Chapter 4: Programming Foundations - Introduction to Python
Initial considerations
Setting up and using anaconda
Getting started with python programming
Important libraries
Conclusion
References and further reading
Chapter 5: Exploring Healthcare Data and clinical Codes
Chapter 6: Preprocessing Healthcare Data in Python
Chapter 7: Machine Learning Algorithms in Python
Chapter 8: Putting It All Together: Developing a Healthcare ML App
Chapter 9: Machine Learning at the Bedside
Chapter 10: Conclusion and Next Steps
Chapter 11:

What You Will Learn

  • Gain valuable background and insight into the healthcare industry.
  • Gets a head-start into predictive healthcare analytics using the powerful Python programming language.
  • It develops a sixth sense for the features and attributes that are important for building successful models in healthcare.
  • Learn about the use-cases that healthcare providers are clamoring to solve.
  • Become an expert with predictive modeling with structured clinical data.

Authors

Table of Contents

Chapter 1: Introduction to Healthcare, Machine Learning, and Software Development
Healthcare delivery in the U.S.
Global healthcare trends
Introduction to patient data
The healthcare machine learning pipeline
Privacy in healthcare
References and further reading
Summary
Chapter 2: Use Cases for Healthcare Machine Learning Apps
Machine learning in healthcare - infinite possibilities
U.S. Government-subsidized use cases
Current machine learning progress for leading causes of mortality
References and further reading
Summary
Chapter 3: Programming Foundations - Introduction to SQL
Introduction
References and Further Reading
Summary
Chapter 4: Programming Foundations - Introduction to Python
Initial considerations
Setting up and using anaconda
Getting started with python programming
Important libraries
Conclusion
References and further reading
Chapter 5: Exploring Healthcare Data and clinical Codes
Chapter 6: Preprocessing Healthcare Data in Python
Chapter 7: Machine Learning Algorithms in Python
Chapter 8: Putting It All Together: Developing a Healthcare ML App
Chapter 9: Machine Learning at the Bedside
Chapter 10: Conclusion and Next Steps
Chapter 11:

Book Details

ISBN 139781787286702
Paperback291 pages
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