TRAIL Score: A Simple Model to Predict Immunochemotherapy Tolerability in Patients With Diffuse Large B-Cell Lymphoma

GameRank: R package for feature selection and construction

MOTIVATION

Building calibrated and discriminating predictive models can be developed through the direct optimization of model performance metrics with combinatorial search algorithms. Often, predictive algorithms are desired in clinical settings to identify patients that may be high and low risk. However, due to the large combinatorial search space, these algorithms are slow and do not guarantee global optimality of their selection.

RESULTS

Here we present a novel and quick maximum-likelihood-based feature selection algorithm, named GameRank. The method is implemented into an R package composed of additional functions to build calibrated and discriminative predictive models.

AVAILABILITY

GameRank is available at https://github.com/Genentech/GameRank and released under the MIT License.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.