Eliminating Bias in Medical Models
Derek emphasizes the importance of eliminating bias in medical models by testing them on external data sets. He highlights the disconnect between the machine learning and medical communities in terms of testing models, stressing the need for robustness and generalization. By addressing this gap, machine learning models can be developed and deployed with more confidence.In this clip
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