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Reinforcement Learning Strategies for Clinical Trials in Nonsmall Cell Lung Cancer

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  • Yufan Zhao
  • Donglin Zeng
  • Mark A. Socinski
  • Michael R. Kosorok

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Suggested Citation

  • Yufan Zhao & Donglin Zeng & Mark A. Socinski & Michael R. Kosorok, 2011. "Reinforcement Learning Strategies for Clinical Trials in Nonsmall Cell Lung Cancer," Biometrics, The International Biometric Society, vol. 67(4), pages 1422-1433, December.
    • Handle: RePEc:bla:biomet:v:67:y:2011:i:4:p:1422-1433
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2011.01572.x
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    References listed on IDEAS

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    1. S. A. Murphy, 2003. "Optimal dynamic treatment regimes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 331-355, May.
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    Citations

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    Cited by:

    1. I Díaz & O Savenkov & K Ballman, 2018. "Targeted learning ensembles for optimal individualized treatment rules with time-to-event outcomes," Biometrika, Biometrika Trust, vol. 105(3), pages 723-738.
    2. Giorgos Bakoyannis, 2023. "Estimating optimal individualized treatment rules with multistate processes," Biometrics, The International Biometric Society, vol. 79(4), pages 2830-2842, December.
    3. Caiyun Fan & Wenbin Lu & Rui Song & Yong Zhou, 2017. "Concordance-assisted learning for estimating optimal individualized treatment regimes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1565-1582, November.
    4. Emily L. Butler & Eric B. Laber & Sonia M. Davis & Michael R. Kosorok, 2018. "Incorporating Patient Preferences into Estimation of Optimal Individualized Treatment Rules," Biometrics, The International Biometric Society, vol. 74(1), pages 18-26, March.
    5. Michael P. Wallace & Erica E. M. Moodie, 2015. "Doubly‐robust dynamic treatment regimen estimation via weighted least squares," Biometrics, The International Biometric Society, vol. 71(3), pages 636-644, September.
    6. Eric B. Laber & Anastasios A. Tsiatis & Marie Davidian & Shannon T. Holloway, 2014. "Discussion of “Combining biomarkers to optimize patient treatment recommendation”," Biometrics, The International Biometric Society, vol. 70(3), pages 707-710, September.
    7. Ying Ding & Bin Nan, 2015. "Estimating Mean Survival Time: When is it Possible?," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 397-413, June.
    8. Huyang Xu & Yuanchen Fang & Chun-An Chou & Nasser Fard & Li Luo, 2023. "A reinforcement learning-based optimal control approach for managing an elective surgery backlog after pandemic disruption," Health Care Management Science, Springer, vol. 26(3), pages 430-446, September.
    9. Zhen Li & Jie Chen & Eric Laber & Fang Liu & Richard Baumgartner, 2023. "Optimal Treatment Regimes: A Review and Empirical Comparison," International Statistical Review, International Statistical Institute, vol. 91(3), pages 427-463, December.
    10. Xin Chen & Rui Song & Jiajia Zhang & Swann Arp Adams & Liuquan Sun & Wenbin Lu, 2022. "On estimating optimal regime for treatment initiation time based on restricted mean residual lifetime," Biometrics, The International Biometric Society, vol. 78(4), pages 1377-1389, December.
    11. Hongming Pu & Bo Zhang, 2021. "Estimating optimal treatment rules with an instrumental variable: A partial identification learning approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(2), pages 318-345, April.

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