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Applied Machine Learning for Healthcare and Life Sciences Using AWS Transformational AI implementations for biotech

      Author: Baturi   |   17 November 2022   |   comments: 0

Applied Machine Learning for Healthcare and Life Sciences Using AWS Transformational AI implementations for biotech
English | 2022 | ISBN: 1804610216 | 224 pages | True PDF | 15.48 MB
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 themExplore AWS machine learning services and their applications in healthcare and life sciencesDiscover practical coding instructions to implement machine learning for healthcare and life sciences
Book 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.
What you will learn
Explore the healthcare and life sciences industryFind out about the key applications of AI in different industry segmentsApply AI to medical images, clinical notes, and patient dataDiscover security, privacy, fairness, and explainability best practicesExplore the AWS ML stack and key AI services for the industryDevelop practical ML skills using code and AWS servicesDiscover all about industry regulatory requirements
Who this book is 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.
Table of Contents
Introducing Machine Learning and the AWS Machine Learning StackExploring Key AWS Machine Learning Services for Healthcare and Life SciencesMachine Learning for Patient Risk StratificationUsing Machine Learning to Improve Operational Efficiency for Healthcare ProvidersImplementing Machine Learning for Healthcare PayorsImplementing Machine Learning for Medical Devices and Radiology ImagesApplying Machine Learning to GenomicsApplying Machine Learning to Molecular DataApplying Machine Learning to Clinical Trials and PharmacovigilanceUtilizing Machine Learning in the Pharmaceutical Supply ChainUnderstanding Common Industry Challenges and SolutionsUnderstanding Current Industry Trends and Future Applications



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