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Invited Talk: Generalizability, robustness and fairness in machine learning risk prediction models
Rumi Chunara

By leveraging principles of health equity, I will discuss the use of causal models and machine learning to address realistic challenges of data collection and model use across environments. Examples include a domain adaptation approach that improves prediction in under-represented population sub-groups by leveraging invariant information across groups when possible, and an algorithmic fairness method which specifically incorporates structural factors to better account for and address sources of bias and disparities.

Author Information

Rumi Chunara (New York University)

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