Fairness and Equity in Machine Learning for Healthcare

Explore fairness and equity in machine learning for healthcare through this insightful conference talk by Irene Chen at the Computational Genomics Summer Institute (CGSI) 2023. Delve into the challenges of equitable healthcare and the role of AI in addressing disparities in general medical and mental health care. Examine evidence of bias through audits and understand why creating equitable healthcare systems is complex. Investigate specific applications of machine learning in healthcare, including intimate partner violence detection and the use of large language models. Learn about the SubLign algorithm's performance in recovering cluster and alignment values on clinical data. Gain valuable insights into why classifiers may exhibit discriminatory behavior and how to address these issues in healthcare AI applications.

Intro
We are Finding Evidence of Bias Through Audits
Why is Equitable Healthcare Challenging?
Machine Learning for Equitable Healthcare
Intimate Partner Violence
How well does SubLign recover cluster and alignment values on clinical data?
Why is My Classifier Discriminatory?
Large Language Models for Equitable Healthcare