Healthcare Analytics Made Simple (Paperback)

Vikas Kumar

ISBN 10: 1787286703 / ISBN 13: 9781787286702

Published by Packt Publishing Limited, Birmingham, 2018

About this Item

Paperback. Add a touch of data analytics to your healthcare systems and get insightful outcomesKey FeaturesPerform healthcare analytics with Python and SQLBuild predictive models on real healthcare data with pandas and scikit-learnUse analytics to improve healthcare performanceBook DescriptionIn 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.What you will learnGain valuable insight into healthcare incentives, finances, and legislation Discover the connection between machine learning and healthcare processesUse SQL and Python to analyze dataMeasure healthcare quality and provider performanceIdentify features and attributes to build successful healthcare models Build predictive models using real-world healthcare dataBecome an expert in predictive modeling with structured clinical dataSee what lies ahead for healthcare analyticsWho this book is forHealthcare 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. Machine learning and analytics have been widely utilized across the healthcare sector of late. This book will bridge the gap between practicing doctors and you as a data scientist. You will learn how to work with healthcare data and gain better insight from this data to improve healthcare outcomes. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9781787286702

Bibliographic Details

• Title: Healthcare Analytics Made Simple (Paperback)
• Publisher: Packt Publishing Limited, Birmingham
• Publication Date: 2018
• Language: English
• ISBN 10: 1787286703
• ISBN 13: 9781787286702
• Binding: Paperback
• Condition: new

About this title

Synopsis

"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"--

About the Author

Dr. Vikas "Vik" Kumar is a physician-turned-Data Scientist from Niskayuna, New York. He earned his MD degree from the University of Pittsburgh, but he discovered his true calling of computers and data science shortly afterward. Dr. Kumar then earned his MS degree from the College of Computing at Georgia Institute of Technology and subsequently began his career as a healthcare data scientist. He has participated in many successful projects related to descriptive, predictive and population health analytics. He currently resides in Atlanta, Georgia, and works as a data scientist at Digital Envoy, a well-established company in the digital marketing industry. 

In addition to being an author, in 2020 Dr. Kumar developed two Health Tech courses with EmergingEd, an education technology company: Health Informatics: Foundations and Frameworks and Health Analytics: Foundations and Frameworks.  He has presented his research and work at many academic conferences and community meetings, including the KDD data science conference and the Data Science ATL Healthcare Analytics Meetup. Dr. Kumar has also appeared in several peer-reviewed journals, including the Journal of the American Medical Informatics Association (JAMIA). 

Dr. Kumar has a BS degree in Neuroscience from Brown University.