Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Applied Machine Learning for Healthcare and Life Sciences using AWS

You're reading from   Applied Machine Learning for Healthcare and Life Sciences using AWS Transformational AI implementations for biotech, clinical, and healthcare organizations

Arrow left icon
Product type Paperback
Published in Nov 2022
Publisher Packt
ISBN-13 9781804610213
Length 224 pages
Edition 1st Edition
Tools
Arrow right icon
Author (1):
Arrow left icon
Ujjwal Ratan Ujjwal Ratan
Author Profile Icon Ujjwal Ratan
Ujjwal Ratan
Arrow right icon
View More author details
Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1: Introduction to Machine Learning on AWS
2. Chapter 1: Introducing Machine Learning and the AWS Machine Learning Stack FREE CHAPTER 3. Chapter 2: Exploring Key AWS Machine Learning Services for Healthcare and Life Sciences 4. Part 2: Machine Learning Applications in the Healthcare Industry
5. Chapter 3: Machine Learning for Patient Risk Stratification 6. Chapter 4: Using Machine Learning to Improve Operational Efficiency for Healthcare Providers 7. Chapter 5: Implementing Machine Learning for Healthcare Payors 8. Chapter 6: Implementing Machine Learning for Medical Devices and Radiology Images 9. Part 3: Machine Learning Applications in the Life Sciences Industry
10. Chapter 7: Applying Machine Learning to Genomics 11. Chapter 8: Applying Machine Learning to Molecular Data 12. Chapter 9: Applying Machine Learning to Clinical Trials and Pharmacovigilance 13. Chapter 10: Utilizing Machine Learning in the Pharmaceutical Supply Chain 14. Part 4: Challenges and the Future of AI in Healthcare and Life Sciences
15. Chapter 11: Understanding Common Industry Challenges and Solutions 16. Chapter 12: Understanding Current Industry Trends and Future Applications 17. Index 18. Other Books You May Enjoy

Surveying the future of AI in healthcare

Researchers are continuously pushing the boundaries of what can be achieved in healthcare and life sciences organizations with the help of AI. Some of these areas are new and experimental, while others have shown promise and are in various stages of prototyping. The following sections detail some of the new and upcoming trends in the future of AI in healthcare and life sciences.

Reinforcement learning

Reinforcement learning is a technique in ML that involves an AI algorithm learning the right sequence of decisions for a problem based on trial and error. An agent evaluates each trial made by the algorithm based on certain rules. The correct decisions made by the algorithm are awarded by the agent, while the incorrect ones are penalized. The overall goal of the algorithm is to maximize the reward. The point to note here is that, unlike supervised learning algorithms where the initial set of correct and incorrect outputs are fed into the...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at £16.99/month. Cancel anytime