Nature

Bayesian Additive Regression Trees

Bayesian Additive Regression Trees (BART) is a nonparametric ensemble method that models complex relationships by summing a collection of decision trees, each operating as a weak learner. The Bayesian ...
JSTOR Daily

A SEMIPARAMETRIC MODELING APPROACH USING BAYESIAN ADDITIVE REGRESSION TREES WITH AN APPLICATION TO EVALUATE HETEROGENEOUS TREATMENT EFFECTS

This is a preview. Log in through your library . Abstract Bayesian Additive Regression Trees (BART) is a flexible machine learning algorithm capable of capturing nonlinearities between an outcome and ...
ascopubs.org

Optimal Donor Selection for Hematopoietic Cell Transplantation Using Bayesian Machine Learning

What Oncologists Want: Identifying Challenges and Preferences on Diagnosis Data Entry to Reduce EHR-Induced Burden and Improve Clinical Data Quality We trained a Bayesian ML model in 10,318 patients ...
JSTOR Daily

Hybridizing Machine Learning Methods and Finite Mixture Models for Estimating Heterogeneous Treatment Effects in Latent Classes

There has been increasing interest in exploring heterogeneous treatment effects using machine learning (ML) methods such as causal forests, Bayesian additive regression trees, and targeted maximum ...
ascopubs.org

Predicting Patient Treatment Deferrals at an Outpatient Chemotherapy Infusion Center: A Statistical Approach

Patients scheduled for outpatient infusion sometimes may be deferred for treatment after arriving for their appointment. This can be the result of a secondary illness, not meeting required bloodwork ...
Medscape

Predicting Non-Responsive Anxiety

The Bayesian Additive Regression Trees (BART) model appears to accurately predict the progression and severity of generalised anxiety disorder (GAD) based on pre-treatment information, potentially ...