“Leveraging Genetics and AI to Improve Alzheimer’s Disease Risk Prediction”

Justin B. Miller, PhD

Director, Pathology Bioinformatics

University of Kentucky College of Medicine

At the completion of this lecture attendees should be able to:

1. Summarize the current state of Alzheimer's disease and Alzheimer's disease genetics.

2. Examine how polygenic risk scores can identify groups of people with increased risk for Alzheimer's disease.

3. Envision how emerging technologies and AI might be used to predict Alzheimer's disease risk.

 Disclosure of Financial Interest Summary to Learners

All planners, faculty, and others in control of educational content are required to disclose all their financial relationships with ineligible companies within the prior 24 months. An ineligible company is defined as one whose primary business is producing, marketing, selling, re-selling, or distributing healthcare products used by or on patients. Financial relationships are relevant if the educational content an individual can control is related to the business lines or products of the ineligible company.

None of the planners, faculty, and others in control of educational content for this educational activity have a relevant financial relationship(s) to disclose with ineligible companies.

The material presented in this course represents information obtained from the scientific literature as well as the clinical experiences of the speakers. In some cases, the presentations might include a discussion of investigational agents and/or off-label indications for various agents used in clinical practice. Speakers will inform the audience when they are discussing investigational and/or off-label uses.

Disclosure of a relationship is not intended to suggest or condone commercial bias in any presentation, but it is made to provide participants with information that might be of potential importance to their evaluation of a presentation