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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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Healthcare and deep learning

No book on healthcare analytics would be complete without a discussion of deep learning. In recent years, unparalleled results have been achieved in the areas of speech recognition, face recognition, language understanding, and object identification using deep learning algorithms (Goodfellow et al., 2016). Almost in tandem have been the breakthroughs in healthcare; from cancer detection on pathology slides and radiology scans to predicting mortality and readmissions, time and time again, results are being seen that rival (and in some cases surpass) committees of expert physicians.

We have already discussed some aspects of deep learning briefly. In Chapter 1, Introduction to Healthcare Analytics, we discussed a historical paper that is seen by many to have been a seminal event for deep learning as a field, in Chapter 3, Machine Learning Foundations...

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