Lecture 2.3.7: Bias, Fairness, and Interpretability in ML

Universal Digital Health · 7:16 · Watch on YouTube

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...

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