Making Healthcare Data Computable with Multimodal Foundation Models

The healthcare and life sciences industry is at an inflection point. Organizations have a wealth of longitudinal patient, member, and claims data that can inform business strategy and improve patient care. At the same time, the rapid adoption of AI is changing how organizations work with large, complex data volumes and shortening time-to-insight. Yet many AI workflows still rely on brittle, one-off pipelines that are difficult to govern, operationalize, or reuse, limiting the value organizations derive from their data and AI investments. 

Join us to learn how multimodal foundation models can turn unstructured clinical histories, notes, labs, images, claims, and payer coding into reusable patient and member assets that support risk prediction, care management, cohort discovery, and outcomes modeling. 

We’ll cover: 
 

• Data and AI trends impacting healthcare and life sciences today 
• How foundation models such as APOLLO for longitudinal patient and member data, can support key industry use cases 
• Practical approaches to patient and member search, cohort exploration, prediction, and attribution 
• And more