Predictive Growth Modeling

Predictive Growth Modeling is a computational or mathematical framework within tumor growth kinetics that quantitatively forecasts future tumor size or behavior based on prior dynamic data, distinguished by its emphasis on forward-looking accuracy and validation against empirical longitudinal observations.

147

Publications

7.3K

Citations

606

Authors

298

Institutions

Publications per year

2017–2026

56

Authors

606

  1. TE
    Thomas E. Yankeelov

    Vanderbilt University, United States

    9 publications · 574 citations

    9

    h-index

  2. SH
    Sang‐Do Ha

    Chung-Ang University, South Korea

    7 publications · 99 citations

    7

    h-index

  3. DA
    David A. Hormuth

    The University of Texas at Austin, United States

    7 publications · 510 citations

    7

    h-index

  4. RM
    Ronald M. Summers

    National Institutes of Health Clinical Center, United States

    6 publications · 313 citations

    6

    h-index

  5. JY
    Jianhua Yao

    National Institutes of Health Clinical Center, United States

    6 publications · 313 citations

    6

    h-index

1–5 of 606

Venues

  1. Journal of Food Protection

    5 publications · 135 citations

    5

    h-index

  2. Cell Proliferation

    4 publications · 278 citations

    4

    h-index

  3. 4

    h-index

  4. Journal of Theoretical Biology

    4 publications · 81 citations

    4

    h-index

  5. Computers in Biology and Medicine

    3 publications · 56 citations

    3

    h-index

1–5