These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

231 related articles for article (PubMed ID: 19750510)

  • 1. Reinforcement learning design for cancer clinical trials.
    Zhao Y; Kosorok MR; Zeng D
    Stat Med; 2009 Nov; 28(26):3294-315. PubMed ID: 19750510
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Reinforcement learning strategies for clinical trials in nonsmall cell lung cancer.
    Zhao Y; Zeng D; Socinski MA; Kosorok MR
    Biometrics; 2011 Dec; 67(4):1422-33. PubMed ID: 21385164
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Reinforcement Learning for Improving Agent Design.
    Ha D
    Artif Life; 2019; 25(4):352-365. PubMed ID: 31697584
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Predicting risk of chemotherapy-induced severe neutropenia: A pooled analysis in individual patients data with advanced lung cancer.
    Cao X; Ganti AK; Stinchcombe T; Wong ML; Ho JC; Shen C; Liu Y; Crawford J; Pang H; Wang X
    Lung Cancer; 2020 Mar; 141():14-20. PubMed ID: 31926983
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep reinforcement learning for automated radiation adaptation in lung cancer.
    Tseng HH; Luo Y; Cui S; Chien JT; Ten Haken RK; Naqa IE
    Med Phys; 2017 Dec; 44(12):6690-6705. PubMed ID: 29034482
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Human locomotion with reinforcement learning using bioinspired reward reshaping strategies.
    Nowakowski K; Carvalho P; Six JB; Maillet Y; Nguyen AT; Seghiri I; M'Pemba L; Marcille T; Ngo ST; Dao TT
    Med Biol Eng Comput; 2021 Jan; 59(1):243-256. PubMed ID: 33417125
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A model to select regimens for phase III trials for patients with advanced-stage non-small cell lung cancer.
    Freidlin B; Breathnach OS; Johnson BE
    Clin Cancer Res; 2003 Mar; 9(3):917-22. PubMed ID: 12631588
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Treatment evaluation for a data-driven subgroup in adaptive enrichment designs of clinical trials.
    Zhang Z; Chen R; Soon G; Zhang H
    Stat Med; 2018 Jan; 37(1):1-11. PubMed ID: 28948633
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Joint modeling of progression-free survival and death in advanced cancer clinical trials.
    Dejardin D; Lesaffre E; Verbeke G
    Stat Med; 2010 Jul; 29(16):1724-34. PubMed ID: 20572123
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Supervised Optimal Chemotherapy Regimen Based on Offline Reinforcement Learning.
    Shiranthika C; Chen KW; Wang CY; Yang CY; Sudantha BH; Li WF
    IEEE J Biomed Health Inform; 2022 Sep; 26(9):4763-4772. PubMed ID: 35714083
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Optimal duration of chemotherapy in advanced non-small cell lung cancer.
    Lustberg MB; Edelman MJ
    Curr Treat Options Oncol; 2007 Feb; 8(1):38-46. PubMed ID: 17634834
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Decision framework for chemotherapeutic interventions for metastatic non-small-cell lung cancer.
    Berthelot JM; Will BP; Evans WK; Coyle D; Earle CC; Bordeleau L
    J Natl Cancer Inst; 2000 Aug; 92(16):1321-9. PubMed ID: 10944554
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep reinforcement learning for optimal experimental design in biology.
    Treloar NJ; Braniff N; Ingalls B; Barnes CP
    PLoS Comput Biol; 2022 Nov; 18(11):e1010695. PubMed ID: 36409776
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Human-level control through deep reinforcement learning.
    Mnih V; Kavukcuoglu K; Silver D; Rusu AA; Veness J; Bellemare MG; Graves A; Riedmiller M; Fidjeland AK; Ostrovski G; Petersen S; Beattie C; Sadik A; Antonoglou I; King H; Kumaran D; Wierstra D; Legg S; Hassabis D
    Nature; 2015 Feb; 518(7540):529-33. PubMed ID: 25719670
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A group sequential Holm procedure with multiple primary endpoints.
    Ye Y; Li A; Liu L; Yao B
    Stat Med; 2013 Mar; 32(7):1112-24. PubMed ID: 23239078
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Integrating temporal difference methods and self-organizing neural networks for reinforcement learning with delayed evaluative feedback.
    Tan AH; Lu N; Xiao D
    IEEE Trans Neural Netw; 2008 Feb; 19(2):230-44. PubMed ID: 18269955
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Building efficient comparative effectiveness trials through adaptive designs, utility functions, and accrual rate optimization: finding the sweet spot.
    Gajewski BJ; Berry SM; Quintana M; Pasnoor M; Dimachkie M; Herbelin L; Barohn R
    Stat Med; 2015 Mar; 34(7):1134-49. PubMed ID: 25640114
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Clinical trials and rare diseases.
    Gerss JW; Köpcke W
    Adv Exp Med Biol; 2010; 686():173-90. PubMed ID: 20824446
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Sequential urn designs with elimination for comparing K > or =3 treatments.
    Coad DS; Ivanova A
    Stat Med; 2005 Jul; 24(13):1995-2009. PubMed ID: 15803441
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Curiosity-driven recommendation strategy for adaptive learning via deep reinforcement learning.
    Han R; Chen K; Tan C
    Br J Math Stat Psychol; 2020 Nov; 73(3):522-540. PubMed ID: 32080828
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.