In this talk, Dave DeCaprio, CTO and co-founder of ClosedLoop will discuss some of the challenges to achieving the promise of machine learning in healthcare, along with some practical approaches he has used to overcome these challenges during his 15 years of data science work in the industry.
Healthcare is often cited as one of the promising areas for machine learning. Healthcare workers are overwhelmed with large amounts of new data becoming available, but are often forced to use antiquated tools to manage that data and make decisions. In particular, Dave will cover how to communicate accuracy and demonstrate the real-world impact in healthcare, and how to address explainability for predictive models. Examples will be drawn from healthcare, but many of the lessons are generally applicable.
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.