Sarah C Van Alsten, Matthew R Dunn, Alina M Hamilton, Joannie M Ivory, Xiaohua Gao, Erin L Kirk, Joseph S Nsonwu-Farley, Lisa A Carey, Yara Abdou, Katherine E Reeder-Hayes, Mya L Roberson, Stephanie B Wheeler, Marc A Emerson, Terry Hyslop, Melissa A Troester
Disparities in OncotypeDx Testing and Subsequent Chemotherapy Receipt by Geography and Socioeconomic Status
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
boosting trees one successful statistical learning approaches involve sequentially growing ensemble simple regression trees weak learners paper proposes gradient boosted trees algorithm spatial data boosts covariate information boosts integrates spatial correlation classical framework extreme gradient boosting tree constructed solving regularized optimization problem objective function takes account underlying spatial correlation involves two penalty terms tree complexity computationallyefficient greedy heuristic algorithm proposed obtain ensemble trees proposed boosts applied spatiallycorrelated fdgpet fluorodeoxyglucosepositron emission tomography imaging data collected clinical trials cancer chemoradiotherapy numerical investigations successfully demonstrate advantages proposed boosts existing approaches particular application