Learn how AI impacts the healthcare ecosystem through real-life case studies with TensorFlow 2.0 and other machine learning (ML) libraries.
This book begins by explaining the dynamics of the healthcare market, including the role of stakeholders such as healthcare professionals, patients, and payers. Then it moves into the case studies. The case studies start with EHR data and how you can account for sub-populations using a multi-task setup when you are working on any downstream task. You also will try to predict ICD-9 codes using the same data. You will study transformer models. And you will be exposed to the challenges of applying modern ML techniques to highly sensitive data in healthcare using federated learning. You will look at semi-supervised approaches that are used in a low training data setting, a case very often observed in specialized domains such as healthcare. You will be introduced to applications of advanced topics such as the graph convolutional network and how you can develop and optimize image analysis pipelines when using 2D and 3D medical images. The concluding section shows you how to build and design a closed-domain Q&A system with paraphrasing, re-ranking, and strong QnA setup. And, lastly, after discussing how web and server technologies have come to make scaling and deploying easy, an ML app is deployed for the world to see with Docker using Flask.
By the end of this book, you will have a clear understanding of how the healthcare system works and how to apply ML and deep learning  tools and techniques to the healthcare industry.


What You Will Learn
Get complete, clear, and comprehensive coverage of algorithms and techniques related to case studies
Look at different problem areas within the healthcare industry and solve them in a code-first approach
Explore and understand advanced topics such as multi-task learning, transformers, and graph convolutional networks
Understand the industry and learn ML


Who This Book Is For
Data scientists and software developers interested in machine learning and its application in the healthcare industry

Product details
ASIN ‏ : ‎ B097XKNTWK
Publisher ‏ : ‎ Apress; 1st ed. edition (July 23, 2021)
Publication date ‏ : ‎ July 23, 2021
Language ‏ : ‎ English
File size ‏ : ‎ 18035 KB
Text-to-Speech ‏ : ‎ Enabled
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 293 pages
Lending ‏ : ‎ Not Enabled