So you've decided to enter the world of analytics, and you know you want to focus on the healthcare industry. However, that barely narrows down the problem space, as there are hundreds of open problems in healthcare that are being addressed with machine learning and other analytical tools. If you have ever typed the words "machine learning in healthcare" into Google or PubMed, you have probably discovered how vast the ocean of machine learning use cases in healthcare is. In academia, publications focus on problems ranging from predicting dementia onset in the elderly to predicting the occurrence of a heart attack within six months to predicting which antidepressants patients will best respond to. How do you pick the problem on which to focus? This section is all about answering that question. Choosing the appropriate problem to...
Healthcare Analytics Made Simple
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Healthcare Analytics Made Simple
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Overview of this book
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 is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed.
By the end of this book, you will understand how to use Python for healthcare 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 through real-world algorithms and code examples.
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Current Title:
Healthcare Analytics Made Simple
Table of Contents (11 chapters)
Preface
Free Chapter
Introduction to Healthcare Analytics
Healthcare Foundations
Machine Learning Foundations
Computing Foundations – Databases
Computing Foundations – Introduction to Python
Measuring Healthcare Quality
Making Predictive Models in Healthcare
Healthcare Predictive Models – A Review
The Future – Healthcare and Emerging Technologies
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