Real-world patient data was not collected with the goal to personalize patient care, yet many attempts to repurpose this data for finding optimal treatments focus on fitting messy, noisy, and biased real-world data into pristine data models. This not only requires expensive and time-consuming cleaning processes but also strips away potentially valuable signals. However, by… Continue reading Embracing the noise and bias in healthcare data