Calibrating predictive model estimates to support personalized medicine.

ABSTRACT:

Objective

Predictive models that generate individualized estimates for medically relevant outcomes are playing increasing roles in clinical care and translational research. However, current methods for calibrating these estimates lose valuable information. Our goal is to develop a new calibration method to conserve as much information as possible, and would compare favorably to existing methods in terms of important performance measures: discrimination and calibration.

Material and methods

We propose an adaptive technique that utilizes individualized confidence intervals (CIs) to calibrate predictions. We evaluate this new method, adaptive calibration of predictions (ACP), in artificial and real-world medical classification problems, in terms of areas under the ROC curves, t

SUBMITTER: Jiang X 

PROVIDER: S-EPMC3277613 | biostudies-literature | 2012 Mar-Apr

REPOSITORIES: biostudies-literature