Fig. 1
From: From algorithms to action: improving patient care requires causality
Illustration of the use of outcome prediction models that ignore treatment allocations in the historical data (i.e. are treatment naive) for treatment decision making. These models change the treatment decisions and thus patient outcomes but whether this change improves patient outcomes is not determined by the prediction accuracy of the outcome prediction model