About this product

Product Identifiers

PublisherPackt Publishing, The Limited

ISBN-101787286703

ISBN-139781787286702

eBay Product ID (ePID)4038567760

Product Key Features

Number of Pages268 Pages

Publication NameHealthcare Analytics Made Simple : Techniques in Healthcare Computing Using Machine Learning and Python

LanguageEnglish

SubjectData Processing, Databases / Data Mining, Programming Languages / Python

Publication Year2018

TypeTextbook

Subject AreaComputers

AuthorVikas (Vik) Kumar

FormatTrade Paperback

Dimensions

Item Length3.6 in

Item Width3 in

Additional Product Features

Intended AudienceTrade

Table Of ContentTable 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

SynopsisMachine 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., 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.