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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

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Product type Paperback
Published in Nov 2022
Publisher Packt
ISBN-13 9781804610213
Length 224 pages
Edition 1st Edition
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Author (1):
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Ujjwal Ratan Ujjwal Ratan
Author Profile Icon Ujjwal Ratan
Ujjwal Ratan
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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

Introducing drug discovery and design

The process of drug discovery and design centers around the identification of biological targets. A disease may demonstrate multiple clinical characteristics, and the goal of the drug compound is to modulate the behavior of the biological entity (such as proteins and genes) that can change the clinical behavior of the disease. This is referred to as the target being druggable. The compounds do this by binding to the target and altering its molecular structure. As a result, understanding the physical structure of the molecule is extremely critical in the drug discovery and design process. Cheminformatics is a branch of science that studies the physical structure as well as the properties of molecules, such as absorption, distribution, metabolism, and extraction (ADME). Targets are screened against millions of compounds based on these properties to find the candidates that can be taken through the steps of clinical research and clinical trials. This...

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