Keith discusses the importance of explainable AI in predicting patient readmissions and suggests using K nearest neighbors to identify similar cases for better insights. He shares an example from an insurance fraud project, highlighting how combining risk scores with supplementary data can enhance decision-making and improve outcomes in complex scenarios.
