Estimating optimal individualized treatment rules with multistate processes

DOI10.1111/biom.13864zbMATH Open1543.62574MaRDI QIDQ6589219

Giorgos Bakoyannis

Publication date: 19 August 2024

Published in: Biometrics (Search for Journal in Brave)

zbMATH Keywords

multistate modelresponseprecision medicinepatient preferencesoutcome-weighted learning

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Support vector regression for right censored data
• Optimal treatment regimes for competing risk data using doubly robust outcome weighted learning with bi-level variable selection
• Optimal treatment regimes for survival endpoints using a locally-efficient doubly-robust estimator from a classification perspective
• Support-vector networks
• Reinforcement Learning Strategies for Clinical Trials in Nonsmall Cell Lung Cancer
• Support Vector Machines
• Estimating Individualized Treatment Rules Using Outcome Weighted Learning
• Optimal Dynamic Treatment Regimes
• A Robust Method for Estimating Optimal Treatment Regimes
• Doubly robust learning for estimating individualized treatment with censored data
• Optimal Structural Nested Models for Optimal Sequential Decisions
• On Estimation of Optimal Treatment Regimes for Maximizing t-Year Survival Probability
• Causal Inference Using Potential Outcomes
• The Elements of Statistical Learning

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