Bayesian additive regression tree (BART) is a recent statistical method that combines
ensemble learning and nonparametric regression. BART is constructed under a probabilistic …

Machine-learning derived algorithms for prediction of radiographic progression in early axial
spondyloarthritis Page 1 Clinical and Experimental Rheumatology 2022 Clinical and …

The Bayesian additive regression trees (BART) model is an ensemble method extensively
and successfully used in regression tasks due to its consistently strong predictive …

In this chapter we provide an overview of the principles and practice of subgroup analysis in
late-stage clinical trials. For convenience, we classify different subgroup analyses into two …

Bayesian additive regression trees (BART) is a Bayesian tree-based model which can
provide high predictive accuracy in both classification and regression problems. Within the …

About 6 years ago, my wife developed an illness that resulted in a loss of short-term
memory. This left her unable to hold a conversation longer than about 10 s. After numerous …

基于Logistic模型的亚组识别方法- PMC Back to Top Skip to main content NIH NLM Logo
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation Preview …

Identifying the sub-population structures along with the tailored treatments for all groups
plays a critical rule for assigning the best available treatment to an individual patient …

Objective We propose a subgroup identification method based on the Logistic model for
data from a two-arm clinical trial with dichotomous outcome variables. In this method, binary …