78 citations · 82 across the 8 of their papers we have counts for
8 papers
MicroSegNet: A Deep Learning Approach for Prostate Segmentation on Micro-Ultrasound Images
Hongxu Jiang, Muhammad Imran, Preethika Muralidharan +12
Micro-ultrasound (micro-US) is a novel 29-MHz ultrasound technique that provides 3-4 times higher resolution than traditional ultrasound, potentially enabling low-cost, accurate di…
Efficient surrogate-assisted inference for patient-reported outcome measures with complex missing mechanism
Jaeyoung Park, Muxuan Liang, Ying-Qi Zhao +1
Patient-reported outcome (PRO) measures are increasingly collected as a means of measuring healthcare quality and value. The capability to predict such measures enables patient-pro…
Robust and flexible learning of a high-dimensional classification rule using auxiliary outcomes
Muxuan Liang, Jaeyoung Park, Qing Lu +1
Correlated outcomes are common in many practical problems. In some settings, one outcome is of particular interest, and others are auxiliary. To leverage information shared by all…
Relative Contrast Estimation and Inference for Treatment Recommendation
Muxuan Liang, Menggang Yu
When there are resource constraints, it is important to rank or estimate treatment benefits according to patient characteristics. This facilitates prioritization of assigning diffe…
Estimation and inference on high-dimensional individualized treatment rule in observational data using split-and-pooled de-correlated score
Muxuan Liang, Young-Geun Choi, Yang Ning +2
With the increasing adoption of electronic health records, there is an increasing interest in developing individualized treatment rules, which recommend treatments according to pat…
Robust Estimation and Variable Selection for the Accelerated Failure Time Model
Yi Li, Muxuan Liang, Lu Mao +1
This paper considers robust modeling of the survival time for cancer patients. Accurate prediction can be helpful for developing therapeutic and care strategies. We propose a unifi…
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…
A Semiparametric Approach to Model Effect Modification
Muxuan Liang, Menggang Yu
One fundamental statistical question for research areas such as precision medicine and health disparity is about discovering effect modification of treatment or exposure by observe…