Cross-validated Survival Models

Cross-Validated Survival Models is a survival modeling methodology that employs cross-validation techniques to assess and optimize the generalizability of survival predictions by systematically partitioning data into training and validation sets to mitigate overfitting and ensure robust performance across diverse cohorts.

47

Publications

4.7K

Citations

401

Authors

141

Institutions

Publications per year

2017–2026

21

Authors

401

  1. HC
    Hans C. van Houwelingen

    Leiden University Medical Center, Netherlands

    4 publications · 2.2K citations

    4

    h-index

  2. SM
    Shigeyuki Matsui

    Nagoya University, Japan

    3 publications · 193 citations

    3

    h-index

  3. RS
    Richard Simon

    National Cancer Institute, United States

    2 publications · 280 citations

    2

    h-index

  4. FE
    Frank E. Harrell

    Vanderbilt University, United States

    2 publications · 194 citations

    2

    h-index

  5. SL
    Saskia le Cessie

    Leiden University Medical Center, Netherlands

    2 publications · 1.7K citations

    2

    h-index

1–5 of 401

Venues

  1. Statistics in Medicine

    6 publications · 675 citations

    6

    h-index

  2. Computers in Biology and Medicine

    2 publications · 83 citations

    2

    h-index

  3. Frontiers in Cardiovascular Medicine

    2 publications · 39 citations

    2

    h-index

  4. Scientific Reports

    2 publications · 87 citations

    2

    h-index

  5. 1

    h-index

1–5