Understanding Current Industry Trends and Future Applications

We have now covered different ways in which ML is making a difference for healthcare and life sciences organizations. With the help of examples in this book, you have seen that ML is more present than you may have thought and is having more impact on the way we live our lives than you may have believed. We have also explored the role AWS is playing in this transformation, particularly how the services from the AWS ML stack are making it easy for healthcare and life sciences customers to innovate at scale. From SageMaker, which lets you build, train, deploy, monitor, and operationalize ML models, to Comprehend Medical, which allows you to extract meaningful information from unstructured clinical records using pretrained models, the services cater to both experienced power users (such as research scientists) and people who are not very familiar with ML and are just getting started. The depth and breadth of these services make...