Main description:

Build real-world artificial intelligence apps on AWS to overcome challenges faced by healthcare providers and payers, as well as pharmaceutical, life sciences research, and commercial organizations

Key Features

Learn about healthcare industry challenges and how machine learning can solve them
Explore AWS machine learning services and their applications in healthcare and life sciences
Discover practical coding instructions to implement machine learning for healthcare and life sciences

Book DescriptionWhile machine learning is not new, it's only now that we are beginning to uncover its true potential in the healthcare and life sciences industry. The availability of real-world datasets and access to better compute resources have helped researchers invent applications that utilize known AI techniques in every segment of this industry, such as providers, payers, drug discovery, and genomics.

This book starts by summarizing the introductory concepts of machine learning and AWS machine learning services. You'll then go through chapters dedicated to each segment of the healthcare and life sciences industry. Each of these chapters has three key purposes -- First, to introduce each segment of the industry, its challenges, and the applications of machine learning relevant to that segment. Second, to help you get to grips with the features of the services available in the AWS machine learning stack like Amazon SageMaker and Amazon Comprehend Medical. Third, to enable you to apply your new skills to create an ML-driven solution to solve problems particular to that segment. The concluding chapters outline future industry trends and applications.

By the end of this book, you'll be aware of key challenges faced in applying AI to healthcare and life sciences industry and learn how to address those challenges with confidence.

What you will learn

Explore the healthcare and life sciences industry
Find out about the key applications of AI in different industry segments
Apply AI to medical images, clinical notes, and patient data
Discover security, privacy, fairness, and explainability best practices
Explore the AWS ML stack and key AI services for the industry
Develop practical ML skills using code and AWS services
Discover all about industry regulatory requirements

Who this book is forThis book is specifically tailored toward technology decision-makers, data scientists, machine learning engineers, and anyone who works in the data engineering role in healthcare and life sciences organizations. Whether you want to apply machine learning to overcome common challenges in the healthcare and life science industry or are looking to understand the broader industry AI trends and landscape, this book is for you. This book is filled with hands-on examples for you to try as you learn about new AWS AI concepts.

Contents:

Table of Contents

Introducing Machine Learning and the AWS Machine Learning Stack
Exploring Key AWS Machine Learning Services for Healthcare and Life Sciences
Machine Learning for Patient Risk Stratification
Using Machine Learning to Improve Operational Efficiency for Healthcare Providers
Implementing Machine Learning for Healthcare Payors
Implementing Machine Learning for Medical Devices and Radiology Images
Applying Machine Learning to Genomics
Applying Machine Learning to Molecular Data
Applying Machine Learning to Clinical Trials and Pharmacovigilance
Utilizing Machine Learning in the Pharmaceutical Supply Chain
Understanding Common Industry Challenges and Solutions
Understanding Current Industry Trends and Future Applications