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Key benefits

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

Description

While 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.

Who is this book for?

This 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.

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

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

Machine Learning with PyTorch and Scikit-Learn

£41.99

Modern Time Series Forecasting with Python

£39.99

Applied Machine Learning for Healthcare and Life Sciences using AWS

£31.99

Total £ 113.97

Sapan P Mar 22, 2023

This book is an excellent guide to implementing ML/AI in biotech, clinical, and healthcare organizations. It is unique for the fact that it focuses specifically on the use of Amazon Web Services (AWS) for machine learning in these industries. The book gradually builds your AWS machine learning knowledge and introduces you to low-code AI services from AWS in a very methodical way. Each chapter is well written and gradually progresses to more advanced topics, and the book covers a range of industry verticals such as providers, payors, pharmaceuticals, genomics, and medical imaging. This book also provides practical knowledge of examples to solidify your knowledge of the concepts learned in each chapter. The best part of the book is that the author uses clear and concise language to explain complex concepts related to machine learning in healthcare and life sciences. While there are other resources available on this topic of ML in healthcare and life sciences which are sparse in nature, this book provides a comprehensive & practical guide to implementing AI using AWS services in this domain.This book can benefit the following individuals the most:1. Business and technology decision-makers who want to understand how machine learning is transforming the healthcare and life sciences industry and the role AWS is playing in that.2. Data scientists, machine learning engineers, and developers who have some prior knowledge of machine learning and are interested in applying it to the healthcare and life sciences industries using AWS.3. Healthcare professionals who want to learn how machine learning can be used to improve patient outcomes, reduce costs, and increase efficiency in healthcare organizations.4. Students or researchers who are interested in the intersection of machine learning, healthcare, and life sciences.Overall, this book is best suited for individuals who have some prior knowledge of machine learning and are interested in applying it to the healthcare and life sciences industries using AWS services.

Amazon Verified review

Vaibhaw K Shende Mar 18, 2023

This book is a valuable resource for anyone looking to create Machine Learning algorithms in Healthcare and Life Sciences domain.One of the strengths of this book is its practical approach. The book provides an overview of healthcare services and then gets into the steps of picking a public dataset, generating a model, and implementing ML on AWS SageMaker. The book is organized into distinct sub-domains in healthcare and life sciences, and each area is explained with potential use cases for applying ML. The also has a ready reference of all the acronyms and datasets used in the healthcare industry.The book introduces functionalities of SageMaker incrementally, like Studio Notebook, Data Wrangler, AutoML, Inference Pipelines for DAG etc, making it less daunting for readers to absorb. The book also does an excellent job of addressing challenges related to applying ML in healthcare, such as bias, encryption, anonymization vs personalization, explainability, auditability etc. It also includes exercises on bias check through SageMaker Clarify.The book also ends with an overview of upcoming trends, including multimodal data, democratization of AI, responsible AI, and healthcare industry-specific trends like Telehealth, digital twins, using IoT & robotics, blockchain, quantum etc.Overall, this book is an easy read with lots of references for additional reading. I highly recommend this book as a practical guide for implementing Machine Learning on the SageMaker platform for use cases in the healthcare domain and life sciences.

Amazon Verified review

Sughosh Gupta Apr 04, 2023

Applied Machine Learning for Healthcare and Life Sciences Using AWS is a well-authored and educational book that provides a wealth of advice. The book is primarily divided into three parts: the first part introduces the reader to machine learning using AWS ML stack; the second part covers machine learning implementation in healthcare industry and the third part covers machine learning applications in the life sciences industry.The book is full of useful information, and it is written in a clear and concise style. The author does a good job of explaining complex concepts in a way that is easy to understand. The book is also full of example code files, datasets, which helps to illustrate the concepts being discussed. If you have an AWS account, you can create sample models as you go along.One of the best features of the book is the focus on practical applications of ML in the healthcare and life sciences industry. The author provides numerous real-world examples from the both the industries that demonstrate how the concepts presented in the book can be applied to solve such problems. One such example is, building data models at scale for risk prediction of deadly diseases, which can help with early detection and timely intervention. This makes the book particularly useful for readers who want to apply what they have learned to their own data science work.Overall, this book is an easy read with lots of references for additional reading. I do recommend having some prior ML knowledge before picking up this book. I highly recommend this book as a practical guide for implementing Machine Learning models using various AWS services for various use cases in the healthcare domain and life sciences industry.

Amazon Verified review

Amazon Customer Feb 14, 2023

It is not very common to find a book like this, it has a very good mixture of AWS and Healthcare/Life science. This adds a lot of value to AWS services in the field of Healthcare.

Amazon Verified review

Megha S. Feb 13, 2023

I am in healthcare industry and I read this book to apply artificial intelligence and machine learning in my work! I highly recommend this book to all health care and biotech people especially strengthen in the pharmaceutical supply chain, and learning in clinical trials and pharmacovigilance.

Amazon Verified review

Applied Machine Learning for Healthcare and Life Sciences using AWS: Transformational AI implementations for biotech, clinical, and healthcare organizations

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