5 papers · 1 filter
BRP-GABLE: An Interpretable Rule-Based Prediction Framework for Multiple Outcome Types
Yulong Li, Ke Wan, Toshio Shimokawa +1
Interpretable prediction models are important in biomedical research, where predictive accuracy must often be balanced against the ability to examine predictor-outcome relationship…
Extention of Bagging MARS with Group LASSO for Heterogeneous Treatment Effect Estimation
Guanwenqing He, Ke Wan, Kazushi Maruo +1
Recent years, large scale clinical data like patient surveys and medical record data are playing an increasing role in medical data science. These large-scale clinical data, collec…
Survival causal rule ensemble method considering the main effect for estimating heterogeneous treatment effects
Ke Wan, Kensuke Tanioka, Toshio Shimokawa
With an increasing focus on precision medicine in medical research, numerous studies have been conducted in recent years to clarify the relationship between treatment effects and p…
Causal rule ensemble method for estimating heterogeneous treatment effect with consideration of main effects
Mayu Hiraishi, Ke Wan, Kensuke Tanioka +2
This study proposes a novel framework based on the RuleFit method to estimate Heterogeneous Treatment Effect (HTE) in a randomized clinical trial. To achieve this, we adopted S-lea…
Rules Ensemble Method with Group Lasso for Heterogeneous Treatment Effect Estimation
Ke Wan, Kensuke Tanioka, Toshio Shimokawa
The increasing scientific attention given to precision medicine based on real-world data has led many recent studies to clarify the relationships between treatment effects and pati…