Calibrating predictive model estimates to support personalized medicine.
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.
Author(s): Jiang, Xiaoqian, Osl, Melanie, Kim, Jihoon, Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2011-000291