Interdisciplinary approach to learn how to identify biases in clinical AI datasets e.g. shortcut features easily learned by computers.
Hands-on session exploring various bias types e.g. measurement bias, and variation in the degree of monitoring from social determinants of care and their impact on AI performance.
