Estimating heterogeneous treatment effects with right-censored data via causal survival forests

27 January 2020

Papers citing "Estimating heterogeneous treatment effects with right-censored data via causal survival forests"

7 / 7 papers shown

Title
CAST: Time-Varying Treatment Effects with Application to Chemotherapy and Radiotherapy on Head and Neck Squamous Cell Carcinoma Everest Yang Ria Vasishtha Luqman K. Dad Lisa A. Kachnic Andrew Hope Eric Wang Xiao Wu Yading Yuan David J. Brenner Igor Shuryak CML 26 0 0 09 May 2025
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations Hammaad Adam Fan Yin Huibin Mary Hu Neil A. Tenenholtz Lorin Crawford Lester W. Mackey Allison Koenecke 22 1 0 20 Jun 2023
Causal survival embeddings: non-parametric counterfactual inference under censoring Carlos García-Meixide Marcos Matabuena CML 38 5 0 20 Jun 2023
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work? Susanne Dandl Torsten Hothorn H. Seibold Erik Sverdrup Stefan Wager A. Zeileis CML 36 11 0 21 Jun 2022
Searching for subgroup-specific associations while controlling the false discovery rate M. Sesia Tianshu Sun 28 0 0 17 May 2022
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Alicia Curth Changhee Lee M. Schaar CML 22 29 0 26 Oct 2021
Causal Interaction Trees: Tree-Based Subgroup Identification for Observational Data Jiabei Yang Issa J. Dahabreh Jon Steingrimsson CML 18 20 0 06 Mar 2020