Development of a Fully Cross-Validated Bayesian Network Approach for Local Control Prediction in Lung Cancer.

ABSTRACT: The purpose of this study is to demonstrate that a Bayesian network (BN) approach can explore hierarchical biophysical relationships that influence tumor response and predict tumor local control (LC) in non-small-cell lung cancer (NSCLC) patients before and during radiotherapy from a large-scale dataset. Our BN building approach has two steps. First, relevant biophysical predictors influencing LC before and during the treatment are selected through an extended Markov blanket (eMB) method. From this eMB process, the most robust BN structure for LC prediction was found via a wrapper-based approach. Sixty-eight patients with complete feature information were used to identify a full BN model for LC prediction before and during the treatment. Fifty more recent patients with some missing informa

SUBMITTER: Luo Y 

PROVIDER: S-EPMC6404542 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature