Healthcare applications are using predictive analytics and machine learning to deliver more value to their end users. With predictive analytics, applications can address hospital readmission rates, prioritize high-risk patients for screening, predict health outcomes for patients, foresee billing issues, and detect fraudulent claims.
Join the webinar to see real-world examples of predictive analytics in healthcare applications. We’ll also give advice on overcoming the top challenges application teams face when they’re embedding predictive analytics.
Common uses of predictive analytics for healthcare applications—including hospital readmissions, patient screenings, and billing issues;
How to handle the most common healthcare data sources; and
How to overcome the top 4 challenges of embedding predictive analytics in applications.