3 citations · 11 across the 13 of their papers we have counts for
14 papers
Longitudinal Random Forests for Sparse and Irregular Response Trajectories
Yangsheng Wang, Xiaotian Dai, Haoda Fu +1
Longitudinal studies often collect data at sparse, irregular, and unequally spaced time points. Such heterogeneity is often driven by subject-specific covariates, yet existing meth…
Unobserved Heterogeneity in Threshold Regression Based on the Hitting Times of a Reflected Brownian Motion for Recurrent Hypoglycemia
Yingfa Xie, Haoda Fu, Yuan Huang +1
Analyses of recurrent hypoglycemia are critical for effective treatment management in diabetic patients. Typically, within-subject dependency in such analyses is captured through s…
Learning Optimal Dynamic Treatment Regimens Subject to Stagewise Risk Controls
Mochuan Liu, Yuanjia Wang, Haoda Fu +1
Dynamic treatment regimens (DTRs) aim at tailoring individualized sequential treatment rules that maximize cumulative beneficial outcomes by accommodating patients' heterogeneity i…
Stabilized Direct Learning for Efficient Estimation of Individualized Treatment Rules
Kushal S. Shah, Haoda Fu, Michael R. Kosorok
In recent years, the field of precision medicine has seen many advancements. Significant focus has been placed on creating algorithms to estimate individualized treatment rules (IT…
Query-augmented Active Metric Learning
Yujia Deng, Yubai Yuan, Haoda Fu +1
In this paper we propose an active metric learning method for clustering with pairwise constraints. The proposed method actively queries the label of informative instance pairs, wh…
Model-Assisted Uniformly Honest Inference for Optimal Treatment Regimes in High Dimension
Yunan Wu, Lan Wang, Haoda Fu
This paper develops new tools to quantify uncertainty in optimal decision making and to gain insight into which variables one should collect information about given the potential c…
Deep Neural Networks Guided Ensemble Learning for Point Estimation
Tianyu Zhan, Haoda Fu, Jian Kang
In modern statistics, interests shift from pursuing the uniformly minimum variance unbiased estimator to reducing mean squared error (MSE) or residual squared error. Shrinkage base…
Near-optimal Individualized Treatment Recommendations
Haomiao Meng, Ying-Qi Zhao, Haoda Fu +1
Individualized treatment recommendation (ITR) is an important analytic framework for precision medicine. The goal is to assign proper treatments to patients based on their individu…
Boosting Algorithms for Estimating Optimal Individualized Treatment Rules
Duzhe Wang, Haoda Fu, Po-Ling Loh
We present nonparametric algorithms for estimating optimal individualized treatment rules. The proposed algorithms are based on the XGBoost algorithm, which is known as one of the…
Multicategory Angle-based Learning for Estimating Optimal Dynamic Treatment Regimes with Censored Data
Fei Xue, Yanqing Zhang, Wenzhuo Zhou +2
An optimal dynamic treatment regime (DTR) consists of a sequence of decision rules in maximizing long-term benefits, which is applicable for chronic diseases such as HIV infection…
Quantile Regression Modeling of Recurrent Event Risk
Huijuan Ma, Limin Peng, Chiung-Yu Huang +1
Progression of chronic disease is often manifested by repeated occurrences of disease-related events over time. Delineating the heterogeneity in the risk of such recurrent events c…
Quantile Regression of Latent Longitudinal Trajectory Features
Huijuan Ma, Limin Peng, Haoda Fu
Quantile regression has demonstrated promising utility in longitudinal data analysis. Existing work is primarily focused on modeling cross-sectional outcomes, while outcome traject…
Estimating Individualized Optimal Combination Therapies through Outcome Weighted Deep Learning Algorithms
Muxuan Liang, Ye Ting, Haoda Fu
With the advancement in drug development, multiple treatments are available for a single disease. Patients can often benefit from taking multiple treatments simultaneously. For exa…
Estimating Individualized Treatment Rules for Ordinal Treatments
Jingxiang Chen, Haoda Fu, Xuanyao He +2
Precision medicine is an emerging scientific topic for disease treatment and prevention that takes into account individual patient characteristics. It is an important direction for…