Visualizing Risk Prediction Models.

ABSTRACT:

Objective

Risk prediction models can assist clinicians in making decisions. To boost the uptake of these models in clinical practice, it is important that end-users understand how the model works and can efficiently communicate its results. We introduce novel methods for interpretable model visualization.

Methods

The proposed visualization techniques are applied to two prediction models from the Framingham Heart Study for the prediction of intermittent claudication and stroke after atrial fibrillation. We represent models using color bars, and visualize the risk estimation process for a specific patient using patient-specific contribution charts.

Results

The color-based model representations provide users with an attractive tool to instantly gauge the relative importa

SUBMITTER: Van Belle V 

PROVIDER: S-EPMC4503430 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature