Diversity Equity and Inclusion in Big Data: How to Recognize Bias in Your AI and Machine Learning Applications

Description

RELEASE DATE: 10/20/2021
EXPIRATION DATE: 10/19/2024

HOW TO COMPLETE THIS ACTIVITY

To complete this activity, learners will watch a webinar (live or recorded) and submit a course evaluation. Once all elements are completed, a certificate will be provided in the Completed Courses section of the My Learning tab.

LEARNING OBJECTIVES

Upon completion of this activity, participants will have strategies to recognize and mitigate bias in artificial intelligence and machine learning applications.

MODERATORS

Edward Quigley, MD, PhD and Noriko Salamon, MD, PhD

AGENDA

Introduction – Edward Quigley, MD, PhD 

Back Pain Management and Utilization in Underserved Populations: A Source for AI to Address Inequity – John Jordan, MD, MPP, FACR 

Why It’s Important for Neuroradiologists to Care About Bias in AI – Ona Wu, PhD 

There’s *No* Bias in Imaging!” A Literature Review – Melissa Davis, MD, MBA 

AI Workflow Tools that Could Address Bias: Non-Image Based AI for Workflow – Ichiro Ikuta, MD, MMSc 

Discussion/Q&A – All faculty

ACCREDITATION STATEMENT

The American Society of Neuroradiology is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

The American Society of Neuroradiology designates this enduring material for a maximum of 1 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

DISCLOSURE INDEX

In compliance with ACCME requirements and guidelines, ASNR has developed a policy for disclosure and review of potential conflicts of interest and a method for resolution if a conflict does exist. ASNR maintains a tradition of scientific integrity and objectivity in its educational activities. In order to preserve these values and ensure its educational activities are independent and free of commercial bias, all individuals, including planners, presenters, moderators and evaluators, participating in an ASNR educational activity, or an activity jointly provided by ASNR must disclose all relevant financial relationships with ineligible companies, as defined by the ACCME.

Wu, Ona: Grant/research support: NIH; Consultant: Penumbra, Genentech; Institutional support: Siemens 

Ikuta, Ichiro: Biogen-sponsored lunch in 2019.

None of the other faculty or planners have relationships to disclose.