Estimating Individualized Treatment Rules Using Outcome Weighted Learning
about
Statistical Methods for Establishing Personalized Treatment Rules in OncologyTreatment decisions based on scalar and functional baseline covariates.Methods for identification and confirmation of targeted subgroups in clinical trials: A systematic reviewDynamic Treatment RegimesInference about the expected performance of a data-driven dynamic treatment regime.Greedy outcome weighted tree learning of optimal personalized treatment rules.Doubly Robust Learning for Estimating Individualized Treatment with Censored DataOptimization of multi-stage dynamic treatment regimes utilizing accumulated dataUsing pilot data to size a two-arm randomized trial to find a nearly optimal personalized treatment strategyTutorial in biostatistics: data-driven subgroup identification and analysis in clinical trials.Regularized outcome weighted subgroup identification for differential treatment effects.Dynamic treatment regimes: technical challenges and applicationsEvaluating marker-guided treatment selection strategies.Doubly Robust Estimation of Optimal Dynamic Treatment Regimes.Estimation of optimal dynamic treatment regimesRejoinder: Combining biomarkers to optimize patient treatment recommendationsDiscussion of combining biomarkers to optimize patient treatment recommendations.Combining biomarkers to optimize patient treatment recommendations.Discussion of "Combining biomarkers to optimize patient treatment recommendation".Q- and A-learning Methods for Estimating Optimal Dynamic Treatment Regimes.A Simple Method for Estimating Interactions between a Treatment and a Large Number of Covariates.On optimal treatment regimes selection for mean survival time.SMART designs in cancer research: Past, present, and future.Evaluating surrogate endpoints, prognostic markers, and predictive markers: Some simple themes.The Fundamental Difficulty With Evaluating the Accuracy of Biomarkers for Guiding TreatmentDesigning a study to evaluate the benefit of a biomarker for selecting patient treatment.A modified classification tree method for personalized medicine decisionsUsing decision lists to construct interpretable and parsimonious treatment regimes.Tree-based methods for individualized treatment regimes.Machine Learning for Treatment Assignment: Improving Individualized Risk Attribution.Estimation of treatment effect in a subpopulation: An empirical Bayes approach.Estimating Optimal Treatment Regimes from a Classification Perspective.Sequential advantage selection for optimal treatment regimePersonalized Evaluation of Biomarker Value: A Cost-Benefit Perspective.Active Clinical Trials for Personalized MedicineSet-valued dynamic treatment regimes for competing outcomes.Identifying predictive markers for personalized treatment selection.Recent development on statistical methods for personalized medicine discovery.Establishing moderators and biosignatures of antidepressant response in clinical care (EMBARC): Rationale and design.General guidance on exploratory and confirmatory subgroup analysis in late-stage clinical trials.
P2860
Q26786366-57D70694-820C-471F-A0D1-AD0452823E10Q27314834-27072A17-EC74-4128-801A-F39A9839B301Q28086970-F1DC83C4-9D2A-4793-956C-9A7190A90382Q30597725-543773FD-82E4-49E3-B098-0FCB9D073206Q30830842-781D36C4-2963-41CD-9720-C377A19D36C5Q30843804-8F5B6C2E-7F26-4E4C-8D99-DCD39B720088Q30943366-4D7FEE67-6FC6-48EF-A53D-9F5DA827B8EFQ30975658-AD79C905-E474-4998-91C0-E193AE3D0789Q31011938-C650AE33-26B6-459F-846E-EEE8B9C4D523Q31119441-6AC1CFBE-F188-42E8-8C66-CE18DF125EEFQ33575291-099B09EA-3BFD-4D7D-89FC-A6C2A6787186Q34406063-C36222FC-66C8-4FF8-8B42-B75E00DFDC11Q34422281-0B95B551-1D31-45B5-ADF5-E543D18453A2Q34577708-565D3A53-7C2D-4E63-B875-9ACFF92FEA36Q34585577-67618BB9-9FE8-4643-B66F-2D220A637090Q34588757-79A66255-51C6-48D4-80E1-56A652A761E5Q34588903-E9A0F458-7B1A-47A6-9270-9728969AC5E7Q34588910-AEB15D0D-81BA-45EA-9B52-A64102E3023BQ34624549-D20C43BA-35CA-424B-BC21-7E44F9D36441Q34990763-6CFD2003-AE70-45AC-A2A5-89E7A2C63802Q35113926-3316E1FA-0716-4634-8A52-B9D544E1E8EEQ35164135-DCAF0C47-8BE9-4F87-8B18-F69716141442Q35607162-ADBC58AE-AAC5-456B-BFC5-BE4A699E202DQ35672166-83E7FFB8-4F49-4904-966F-3408D3CED41CQ36173510-9FE291E1-1D95-4B64-ACBB-EDEBE29DF135Q36225623-AED07AE8-4DA8-4C1B-9EBD-155E877E492BQ36449319-D8E3AA4F-DE8E-4C15-A479-DDC31A31E754Q36470116-C5CF8C52-2BA7-4D90-A06C-E88D7422E9DCQ36584831-EA8BB863-C97C-459C-B53B-CAC80822B01DQ36613424-0069E37E-ED91-45C1-A64A-B7F8BFB5AD24Q36746642-647CB33C-7D51-4206-B10B-B5B2AAF59EC6Q36806557-4363A39E-5F39-4082-9F7E-3A65AFDD636DQ37016184-75912573-91DB-498B-9D05-EA52AD3944E7Q37079999-DC122D35-4AE2-4DCE-A24D-0DB1F7ED6028Q37527735-E6C009A2-1935-4EB4-8833-299535637868Q37637697-0F9EADF3-A9EF-457D-B70E-11F3E5279684Q37702844-9DEFC5ED-8BEA-417A-A5E6-E8F4DD73A0CBQ38078840-FE6C092F-8DE5-4BD9-81A8-F6A28BCDBEC4Q38394152-3DA6C5A2-2E64-4CE0-9C83-F1304D08E157Q38586261-E199BD7D-6553-4CCF-B4B9-13279B605EF4
P2860
Estimating Individualized Treatment Rules Using Outcome Weighted Learning
description
2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
2012年论文
@zh
2012年论文
@zh-cn
name
Estimating Individualized Treatment Rules Using Outcome Weighted Learning
@en
type
label
Estimating Individualized Treatment Rules Using Outcome Weighted Learning
@en
prefLabel
Estimating Individualized Treatment Rules Using Outcome Weighted Learning
@en
P2093
P2860
P1476
Estimating Individualized Treatment Rules Using Outcome Weighted Learning
@en
P2093
Donglin Zeng
Michael R Kosorok
Yingqi Zhao
P2860
P304
P356
10.1080/01621459.2012.695674
P407
P577
2012-09-01T00:00:00Z