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.
Predict the comprehensive chronic and preventive care needs of individual patients with unparalleled precision.
Predict and prioritize high-risk members and use Contributing Factors insights to personalize outreach and interventions.
Strengthen commercial success, gain precision insights into key cohorts, and power digital therapeutics and value-based contracts.