Healthcare Analytics Made Simple
暫譯: 簡單易懂的醫療分析

Key Features

• Bring IT and Analytics for Healthcare to routine practice with this example-rich guide.
• Gain better insights into healthcare workflow, treatment, and optimize money involved.
• It Bridges the gap between the theory of machine learning and needs of the healthcare community.
• Perform efficient programming and analytics for healthcare business

Book Description

This book is a self-contained overview of machine learning for healthcare analytics. Book describes briefly the current international healthcare landscape, machine learning algorithms, and the Python programming language.Application of these principles to popular healthcare analytic use-cases that healthcare providers are clamoring to solve, such as readmission prediction and emergency department outcome evaluation etc. Each chapter will cover a new use-case with a new machine learning algorithm and will develop step-by-step code sufficient for implementation.

The functional outcomes of the book is to demonstrate that how Python packages are used for 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, with the help of real-world examples.

What you will learn

• Gain valuable background and insight into the healthcare industry.
• Gets a head-start into predictive healthcare analytics using the powerful Python programming language.
• It develops a sixth sense for the features and attributes that are important for building successful models in healthcare.
• Learn about the use-cases that healthcare providers are clamoring to solve.
• Become an expert with predictive modeling with structured clinical data.