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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

Product type Paperback

Published in Nov 2022

Publisher Packt

ISBN-13 9781804610213

Length 224 pages

Edition 1st Edition

Tools

AWS

Concepts

Machine Learning

Author (1):

Ujjwal Ratan

View More author details

Table of Contents (19) Chapters

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

Why subscribe?

18. Other Books You May Enjoy

Further reading

Magic Quadrant for Cloud Infrastructure and Platform Services by Raj Bala, Bob Gill, Dennis Smith, David Wright, Kevin Ji in Gartner (2021): https://www.gartner.com/doc/reprints?id=1-271OE4VR&ct=210802&st=sb
Solution Scorecard for Amazon SageMaker by Daniel Cota, Su En Goh in Gartner (2021): https://www.gartner.com/en/documents/4002618
AWS Healthcare & Life Sciences Case Studies: https://aws.amazon.com/health/case-studies/?nc=sn&loc=5&refid=ar_card&case-studies-health-cards.sort-by=item.additionalFields.publishedDate&case-studies-health-cards.sort-order=desc&awsf.case-studies-filter-area=*all
UK Biobank: https://www.ukbiobank.ac.uk/
Centers for Medicare & Medicaid Services: https://www.cms.gov/medicare/icd-10/2021-icd-10-cm
RxNorm Files: https://www.nlm.nih.gov/research/umls/rxnorm/docs/rxnormfiles.html
SNOMED: https://www.snomed.org/snomed-ct/why-snomed-ct
Amazon Comprehend Medical: https://docs.aws...

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Authors (1)

Ujjwal Ratan

Ujjwal Ratan

Ujjwal is a Principal AI/Machine Learning Solutions Architect at AWS where he leads the machine learning solutions architecture group dedicated to healthcare and life sciences. Over the years, Ujjwal has been a thought leader in the healthcare and life sciences industry, helping multiple Global Fortune 500 organizations achieve their innovation goals by adopting machine learning. His work involving the analysis of medical imaging, unstructured clinical text and genomics has helped AWS build products and services that provide highly personalized and precisely targeted diagnostics and therapeutics. Ujjwal's work has also been featured in multiple global conferences, peer-reviewed publications or technical and scientific blogs.

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