Regularized Survival Models

Regularized Survival Models is a class of statistical models in survival analysis that incorporates penalty terms to constrain model complexity, thereby improving generalization by reducing overfitting in the estimation of time-to-event outcomes.

41

Publications

3K

Citations

142

Authors

88

Institutions

Publications per year

2017–2026

16

Variants

Penalized Survival Models

Authors

142

  1. TH
    Trevor Hastie

    Stanford University, United States

    3 publications · 71 citations

    3

    h-index

  2. CK
    Chandan K. Reddy

    Virginia Tech, United States

    3 publications · 125 citations

    3

    h-index

  3. JQ
    Junyang Qian

    Stanford University, United States

    2 publications · 51 citations

    2

    h-index

  4. SV
    Susana Vinga

    Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento, Portugal

    2 publications · 44 citations

    2

    h-index

  5. RS
    Randall S. Burd

    Children's National, United States

    2 publications · 61 citations

    2

    h-index

1–5 of 142

Venues

  1. Biometrics

    4 publications · 153 citations

    4

    h-index

  2. Biostatistics

    3 publications · 106 citations

    3

    h-index

  3. Lifetime Data Analysis

    2 publications · 49 citations

    2

    h-index

  4. Statistics in Medicine

    2 publications · 64 citations

    2

    h-index

  5. Computers in Biology and Medicine

    2 publications · 35 citations

    2

    h-index

1–5