It’s not enough for predictive models to be accurate, they must also be explainable. One of the main barriers to adopting artificial intelligence for hospitals and clinicians is their concern it’s a “black box” making it difficult to trust the results. Andrew Eye joins the DataPoint podcast and explains how ClosedLoop unpacks the “black box” of AI by allowing data scientists and clinicians to understand why and how factors impact a models prediction, driving faster adoptions and better clinical results.
Interested in learning more about how healthcare leaders are leveraging AI and the importance of explainability? Check out these related resources: