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Healthcare Analytics Made Simple

Healthcare Analytics Made Simple

By : Kumar, Khader
4.4 (8)
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Healthcare Analytics Made Simple

Healthcare Analytics Made Simple

4.4 (8)
By: Kumar, Khader

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.
Table of Contents (11 chapters)
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Introduction to databases

A database can be defined as a collection of related data (Elmasri and Navathe, 2010). Databases are often subcategorized as SQL databases or NoSQL databases. In SQL databases, data is recorded in tables and consists of rows and columns. The related data may be distributed across several tables in a trade-off between efficient storage and convenience. The database management system (DBMS) is a piece of software that enables the database to serve several functions. For one thing, it allows for the retrieval of data using the SQL language (for SQL databases). Another function is to update the data when needed, also using SQL. Additional functions of a DBMS include protecting and securing the data.

Database management is a complex field of its own. In this book, we will place an emphasis on using SQL to retrieve and update clinical data that is usually distributed...

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