Machine Learning and AI for Payer, Provider and Government Organizations

  • 10 Oct 2018
  • 9:00 AM - 11:00 AM
  • MHDC Offices and Online


  • Members may attend the talk in person - space is limited!
  • Members may attend online if preferred
  • Non Members may attend online presentation.

Registration is closed

Machine Learning and AI for Payer, Provider and Government Organizations

A technology and application overview of Machine Learning (ML) and Artificial Intelligence (AI) applications in healthcare analytics, showing three complete ML Apps on the Smart decisions ML & AI Platform from Edifecs. The presentation will help payers and providers understand the role and use cases of Machine Learning for Data Analytics and their applications to healthcare.

There is broad agreement in the industry and among research communities, that ML (in conjunction with AI) will significantly alter and improve healthcare. In this discussion, we will focus on three ML and AI use cases relevant to payers and providers from the point of view of four stakeholders:

  • Health Plan
  • Provider (or clinic / hospital)
  • Government (State/ CMS)
  • Member

To this end, we will introduce Machine Learning, its essential methods and algorithms, and the types of technology tools used. We will also discuss the relationships among ML, AI, statistics and traditional Business Intelligence (BI). Using select payer and provider use cases, we will discuss how a healthcare business use case is designed as a combination of datasets and algorithms as bridges to ML and AI, and how such algorithms can be implemented (in R) and used to enrich the analytics practice within healthcare. 

Lessons to Be Learned:

  • What foundational technology pieces are required to benefit from Machine Learning and Artificial Intelligence?
  • What does an effective Data Science team look like?
  • Which use cases can greatly benefit from Machine Learning and AI?
  • What type of data is required to execute certain types of use cases?
  • Prasad Saripalli, Vice President – Data Science, Edifecs Inc.
  • Paul Dausman, Senior Director – Data Science, Edifecs Inc.

Massachusetts Health Data Consortium
460 Totten Pond Road | Suite 690
Waltham, Massachusetts 02451

For more information,
please contact Arleen Coletti
by email or at 781.419.7818

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