Modeling Individual-Level Uncertainty From Missing Data in Multifactorial Breast Cancer Risk Prediction
Bethan White, Lorenzo Ficorella, X Yang, K Czene et autres
PURPOSE: Multifactorial breast cancer (BC) risk prediction models use a range of predictors to estimate an individual's chance of developing BC. Data on risk factors are often incomplete, and point estimates calculated when data are missing can mask considerable uncertainty. Quantifying this …
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