November 2022
Intermediate to advanced
224 pages
6h 48m
English
Content preview from Applied Machine Learning for Healthcare and Life Sciences using AWS
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3
Machine Learning for Patient Risk Stratification
Chapters 1 and 2 were foundational chapters that were designed to help you get introduced to the concepts of ML, its applications in healthcare and life sciences, and also some key services from AWS. With this foundational knowledge, we can now start applying these techniques to real-world industry problems. Over the course of the next eight chapters, you will learn about specific applications of AI/ML for solving problems for healthcare providers, payers, pharma, medical devices, and genomics customers.
In this chapter, we will look at one of the most common usages of ML in healthcare, the stratification or identification of risky patients. We will learn what it takes to identify risky patients ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.