Multivariate Screening Models

Multivariate Screening Models is a statistical framework in prenatal risk assessment that integrates multiple biomarkers and clinical variables into a single predictive model to estimate the probability of specific fetal abnormalities, distinguishing itself from univariate or sequential screening approaches by simultaneously analyzing diverse risk factors within a unified algorithm.

93

Publications

4.9K

Citations

646

Authors

217

Institutions

Publications per year

2017–2026

29

Authors

646

  1. MP
    M. Pilar Callao

    Universitat Rovira i Virgili, Spain

    3 publications · 136 citations

    3

    h-index

  2. IR
    Itziar Ruisánchez

    Universitat Rovira i Virgili, Spain

    3 publications · 136 citations

    3

    h-index

  3. BR
    Bianca Russell

    University of California, Los Angeles, United States

    2 publications · 60 citations

    2

    h-index

  4. TM
    Thomas Minten

    Harvard University, United States

    2 publications · 60 citations

    2

    h-index

  5. NS
    Nik Sumikawa

    University of California, Santa Barbara, United States

    2 publications · 56 citations

    2

    h-index

1–5 of 646

Venues

  1. PubMed

    Repository · 4 publications · 85 citations

    4

    h-index

  2. PLoS ONE

    3 publications · 101 citations

    3

    h-index

  3. American Journal of Public Health

    JPH · 2 publications · 164 citations

    2

    h-index

  4. Analytica Chimica Acta

    2 publications · 67 citations

    2

    h-index

  5. PEDIATRICS

    2 publications · 149 citations

    2

    h-index

1–5