Progression Pattern Discovery

Progression Pattern Discovery is a computational methodology within longitudinal phenotype trajectory analysis that identifies distinctive temporal patterns of phenotypic change by distinguishing underlying disease or trait progression dynamics from individual variability and noise.

37

Publications

2K

Citations

368

Authors

162

Institutions

Publications per year

2017–2026

26

Authors

368

  1. SK
    Sylvia K. Plevritis

    Stanford University, United States

    1 publications · 57 citations

    1

    h-index

  2. PA
    P. A. Wijeratne

    University College London, United Kingdom

    1 publications · 82 citations

    1

    h-index

  3. KS
    Karen Sachs

    Stanford University, United States

    1 publications · 52 citations

    1

    h-index

  4. KF
    Kazuo Fujihara

    Tohoku University, Japan

    1 publications · 32 citations

    1

    h-index

  5. KJ
    Kee‐Taek Jang

    Samsung Medical Center, South Korea

    1 publications · 44 citations

    1

    h-index

1–5 of 368

Venues

  1. Scientific Reports

    2 publications · 60 citations

    2

    h-index

  2. Journal of Biomedical Informatics

    1 publications · 11 citations

    1

    h-index

  3. Clinical Lung Cancer

    1 publications · 26 citations

    1

    h-index

  4. Neurology

    1 publications · 452 citations

    1

    h-index

  5. Translational Neurodegeneration

    1 publications · 17 citations

    1

    h-index

1–5