Summary
In this chapter, we looked at some of the challenges that technologists face when implementing ML workflows in the healthcare and life sciences industry. These include regulatory challenges, security and privacy, and ensuring fairness and generalizability. We also looked at ways that organizations are addressing those challenges. We then learned about SageMaker Clarify and Model Monitor, and how they ensure fairness and provide explainability for ML models. Finally, we used SageMaker Clarify to create a bias and explainability report for a model that predicts healthcare coverage amounts.
In Chapter 12, Understanding Current Industry Trends and Future Applications, we will paint a picture of what to expect in the future for AI in healthcare. We will look at some newer innovations in this field and conclude by summarizing some trends.
