Learning Optimal Personalized Treatment Rules in Consideration of Benefit and Risk: With an Application to Treating Type 2 Diabetes Patients With Insulin Therapies

DOI10.1080/01621459.2017.1303386zbMath1398.62349OpenAlexW2599189192WikidataQ90399062 ScholiaQ90399062MaRDI QIDQ4690922

Donglin Zeng, Yuanjia Wang, Haoda Fu

Publication date: 23 October 2018

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc6051551

zbMATH Keywords

machine learningNeyman-Pearson lemmapersonalized medicinehypoglycemiabenefit-risk analysis

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

Related Items (9)

Statistical inference in massive datasets by empirical likelihood ⋮ A Two-Part Framework for Estimating Individualized Treatment Rules From Semicontinuous Outcomes ⋮ Estimating individualized treatment rules with risk constraint ⋮ Fairness-Oriented Learning for Optimal Individualized Treatment Rules ⋮ Estimating the optimal individualized treatment rule from a cost‐effectiveness perspective ⋮ Optimal Treatment Regimes: A Review and Empirical Comparison ⋮ Bayesian Nonparametric Policy Search With Application to Periodontal Recall Intervals ⋮ Unnamed Item ⋮ Unnamed Item

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