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    Healthcare Analytics Made Simple: Techniques in healthcare computing using machine learning and Python

    Posted By: AlenMiler
    Healthcare Analytics Made Simple: Techniques in healthcare computing using machine learning and Python

    Healthcare Analytics Made Simple: Techniques in healthcare computing using machine learning and Python by Vikas (Vik) Kumar
    English | 31 July 2018 | ISBN: 1787286703 | 268 Pages | EPUB | 2.28 MB

    Add a touch of data analytics to your healthcare systems and get insightful outcomes

    Key Features
    Perform healthcare analytics with Python and SQL
    Build predictive models on real healthcare data with pandas and scikit-learn
    Use analytics to improve healthcare performance
    Book Description
    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.

    What you will learn
    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
    Build predictive models using real-world healthcare data
    Become an expert in predictive modeling with structured clinical data
    See what lies ahead for healthcare analytics
    Who this book is for
    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.

    Table of Contents
    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