Personalized dynamic treatment regimes in continuous time: a Bayesian approach for optimizing clinical decisions with timing
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Publication:6121782
DOI10.1214/21-ba1276arXiv2007.04155OpenAlexW3183923748WikidataQ114599201 ScholiaQ114599201MaRDI QIDQ6121782
Sarah Zohar, Yanxun Xu, William Hua, Magali Giral, Hongyuan Mei
Publication date: 27 February 2024
Published in: Bayesian Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2007.04155
policy gradientelectronic health recordsdynamic treatment regimesmarked temporal point processBayesian joint model
Cites Work
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- Statistical methods for dynamic treatment regimes. Reinforcement learning, causal inference, and personalized medicine
- Dynamic treatment regimes: technical challenges and applications
- Survival and event history analysis. A process point of view
- Simple statistical gradient-following algorithms for connectionist reinforcement learning
- A Bayesian analysis of some nonparametric problems
- Exact Simulation of Point Processes with Stochastic Intensities
- Reinforcement Learning Strategies for Clinical Trials in Nonsmall Cell Lung Cancer
- Modeling associations between latent event processes governing time series of pulsing hormones
- The Robust Inference for the Cox Proportional Hazards Model
- Optimal Dynamic Treatment Regimes
- A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect
- Bayesian Nonparametric Policy Search With Application to Periodontal Recall Intervals
- Estimating Dynamic Treatment Regimes in Mobile Health Using V-Learning
- Enhancing human learning via spaced repetition optimization
- Doubly robust learning for estimating individualized treatment with censored data
- Joint Models for Multivariate Longitudinal and Multivariate Survival Data
- Spectra of some self-exciting and mutually exciting point processes
- A Stochastic Approximation Method
- Learning When-to-Treat Policies
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