Discrimination Metrics

Discrimination Metrics is a statistical evaluation framework used in polygenic risk assessment that quantifies the ability of a risk model to distinguish between individuals with and without a particular trait or disease outcome based on genetic predisposition.

207

Publications

16.1K

Citations

597

Authors

329

Institutions

Publications per year

2017–2026

38

Authors

597

  1. MP
    Michael Pencina

    Boston University, United States

    7 publications · 1.1K citations

    7

    h-index

  2. RB
    Ralph B. D’Agostino

    Boston University, United States

    6 publications · 1.1K citations

    6

    h-index

  3. SK
    S. Kullback

    George Washington University, United States

    5 publications · 155 citations

    5

    h-index

  4. JL
    Jialiang Li

    National University of Singapore, Singapore

    4 publications · 122 citations

    4

    h-index

  5. JP
    Jason P. Fine

    University of North Carolina at Chapel Hill, United States

    4 publications · 155 citations

    4

    h-index

1–5 of 597

Venues

  1. Statistics in Medicine

    15 publications · 1.4K citations

    15

    h-index

  2. PubMed

    Repository · 6 publications · 309 citations

    6

    h-index

  3. Psychological Bulletin

    6 publications · 1.3K citations

    6

    h-index

  4. Biometrics

    5 publications · 476 citations

    5

    h-index

  5. Journal of Experimental Psychology

    5 publications · 215 citations

    5

    h-index

1–5