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When accurate prediction models yield harmful self-fulfilling prophecies
These models are harmful self-fulfilling prophecies: their deployment harms a group of patients but the worse outcome of these patients does not invalidate the predictive power of the model.
From algorithms to action: improving patient care requires causality
In cancer research there is much interest in building and validating outcome predicting outcomes to support treatment decisions.
Controlling for Biasing Signals in Images for Prognostic Models: Survival Predictions for Lung Cancer with Deep Learning
This is achieved by (1) setting a dual task for the network to predict both the outcome and the collider and (2) enforcing independence of the activation distributions of the last layer with ordinary least squares.
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