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Explainable AI (xAI)
for Medicare Advantage

Machine learning backed decisions are not enough to meet the need of healthcare today. xAI, or Explainable AI is what we need.

In a highly regulated industry like healthcare, we cannot blindly believe the results we are presented. xAI is what solves this problem and in this webinar we will deep dive into what it is and how it helps healthcare providers.

Payors will get an understanding of how xAI will benefit their strategic decision making for product, provider networks and marketing. They will also get a better understating of how such an exercise is executed and what are the different methodologies that are used.

In this webinar, attendees will learn:

Webinar Details

Date: January 19, 2022
Time: 2 PM EST/11 AM PST
Duration: 45 Minutes plus live Q & A

This educational webinar will focus on the application of xAI in healthcare marketing, with emphasis on how Payers and Providers can measure the impact of individual variables to increase marketing ROI.

While traditional Black Box AI models typically provide better prediction accuracy, the lack of explainability, or comprehension of the driving factors, often leaves marketers struggling to find ways to exceed predictions. Explainable AI, or xAI for short, provides that much-needed granularity.

In addition to reviewing the various xAI methods, we’ll discuss how detailed factors, such as channel spend, product/brand positioning, contact volume, segment targeting, and campaign timing, can each be analyzed and assigned a significance score based on their contribution toward enrollment. With this scoring in place, marketers can capitalize on industry trends, and the success of others, to maximize potential, and gain an unfair share of the market.


Jereme Ayers

Chief Growth Officer

Jereme represents the voice-of-the-customer and ensures each product, service, and research analysis provides a solution for the unique challenges of the Medicare Advantage market. As a practitioner in the Medicare Advantage and analytics space, Jereme focuses on the implementation of advanced analytics and strategic operationalization of data to enable a data-driven methodology.

Shreya Mukhopadhyay

Lead - Data Sciences

Shreya is an analytics professional with more than six years of experience in statistical model development and data consultation. She has worked on cutting-edge machine learning algorithms that enable businesses to make better decisions by turning raw data into actionable insights. Her areas of expertise include python, R statistical computing, data exploration, and visualization.

Roydon Noronha

Sr. Business Analyst – Market Research

Roydon Noronha, lead researcher for our healthcare analytics group, provides key market insights to leadership to enable enhanced market strategies through advance analytics and Business Intelligence tools with a goal of better understanding the vast and complex data of the Medicare Advantage.
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