Lecture 2.3.7: Bias, Fairness, and Interpretability in ML
Universal Digital Health · 7:16
This lecture introduces three linked ideas in healthcare machine learning: bias (systematic errors that come from data, measurement, or the algorithm), fairness (metrics that check a model doesn't discriminate across...