Tree-based Subgroup Discovery In Electronic Health Records: Heterogeneity of Treatment Effects for DTG-containing Therapies

no code implementations • 30 Aug 2022 • Jiabei Yang, Ann W. Mwangi, Rami Kantor, Issa J. Dahabreh, Monicah Nyambura, Allison Delong, Joseph W. Hogan, Jon A. Steingrimsson

The rich longitudinal individual level data available from electronic health records (EHRs) can be used to examine treatment effect heterogeneity.

Subgroup Discovery

Inference for BART with Multinomial Outcomes

1 code implementation • 18 Jan 2021 • Yizhen Xu, Joseph W. Hogan, Michael J. Daniels, Rami Kantor, Ann Mwangi

The multinomial probit Bayesian additive regression trees (MPBART) framework was proposed by Kindo et al. (KD), approximating the latent utilities in the multinomial probit (MNP) model with BART (Chipman et al. 2010).

Classification using Ensemble Learning under Weighted Misclassification Loss

1 code implementation • 16 Dec 2018 • Yizhen Xu, Tao Liu, Michael J. Daniels, Rami Kantor, Ann Mwangi, Joseph W. Hogan

Binary classification rules based on covariates typically depend on simple loss functions such as zero-one misclassification.

Binary Classification Classification +2