no code implementations • 13 Dec 2019 • Naim U. Rashid, Daniel J. Luckett, Jingxiang Chen, Michael T. Lawson, Longshaokan Wang, Yunshu Zhang, Eric B. Laber, Yufeng Liu, Jen Jen Yeh, Donglin Zeng, Michael R. Kosorok
PDX data are characterized by correlated outcomes, a high-dimensional feature space, and a large number of treatments.
no code implementations • 30 Oct 2020 • Yuan Chen, Donglin Zeng, Tianchen Xu, Yuanjia Wang
This learning framework is based on the measurement theory in psychiatry for modeling multiple disease diagnostic measures as arising from the underlying causes (true mental states).
no code implementations • NeurIPS 2020 • Yuan Chen, Donglin Zeng, Tianchen Xu, Yuanjia Wang
This learning framework is based on the measurement theory in psychiatry for modeling multiple disease diagnostic measures as arising from the underlying causes (true mental states).
no code implementations • NeurIPS 2021 • Yuan Chen, Wenbo Fei, Qinxia Wang, Donglin Zeng, Yuanjia Wang
COVID-19 pandemic has caused unprecedented negative impacts on our society, including further exposing inequity and disparity in public health.
no code implementations • 25 Feb 2022 • Lin Ge, Xinming An, Donglin Zeng, Samuel McLean, Ronald Kessler, Rui Song
Adverse posttraumatic neuropsychiatric sequelae (APNS) are common among veterans and millions of Americans after traumatic exposures, resulting in substantial burdens for trauma survivors and society.
no code implementations • 29 Jan 2023 • Daiqi Gao, Yufeng Liu, Donglin Zeng
Dynamic treatment rules or policies are a sequence of decision functions over multiple stages that are tailored to individual features.
no code implementations • 25 Jan 2024 • Xingche Guo, Donglin Zeng, Yuanjia Wang
To measure reward processing, patients perform computer-based behavioral tasks that involve making choices or responding to stimulants that are associated with different outcomes.
1 code implementation • 13 Feb 2024 • Daiqi Gao, Yuanjia Wang, Donglin Zeng
Therefore, our objective is to learn an ITR that not only maximizes the value function for the primary outcome, but also approximates the optimal rule for the secondary outcomes as closely as possible.