Bayesian Dose-finding

Bayesian Dose-Finding is a statistical methodology within clinical trial design that uses Bayesian inference to sequentially update the probability of dose-toxicity and dose-efficacy relationships, thereby identifying an optimal dose by synthesizing accumulating trial data with prior knowledge.

127

Publications

7.5K

Citations

359

Authors

195

Institutions

Publications per year

2017–2026

36

Variants

Bayesian Dose-finding Design

Authors

359

  1. YY
    Ying Yuan

    The University of Texas MD Anderson Cancer Center, United States

    23 publications · 1.8K citations

    18

    h-index

  2. PF
    Peter F. Thall

    The University of Texas MD Anderson Cancer Center, United States

    13 publications · 1.4K citations

    13

    h-index

  3. SZ
    Sarah Zohar

    Inserm, France

    11 publications · 391 citations

    10

    h-index

  4. YJ
    Yuan Ji

    Endeavor Health, United States

    9 publications · 821 citations

    9

    h-index

  5. GY
    Guosheng Yin

    University of Hong Kong, Hong Kong SAR China

    9 publications · 910 citations

    9

    h-index

1–5 of 359

Venues

  1. Statistics in Medicine

    27 publications · 1.4K citations

    20

    h-index

  2. Biometrics

    15 publications · 1.9K citations

    15

    h-index

  3. Journal of Biopharmaceutical Statistics

    JBS · 11 publications · 440 citations

    11

    h-index

  4. 9

    h-index

  5. Pharmaceutical Statistics

    8 publications · 300 citations

    8

    h-index

1–5