Multiple Biomarker Modeling

Multiple Biomarker Modeling is a computational or statistical framework designed to simultaneously analyze and integrate multiple biomarkers to improve disease characterization, prediction, or treatment response assessment, distinguishing it from single biomarker approaches by capturing multivariate biological interactions and dependencies.

28

Publications

2K

Citations

177

Authors

91

Institutions

Publications per year

2017–2026

14

Variants

Multimarker Modeling

Authors

177

  1. GF
    Guido Ferrari

    Duke Medical Center, United States

    1 publications · 147 citations

    1

    h-index

  2. DS
    Douglas S. Scherr

    Cornell University, United States

    1 publications · 54 citations

    1

    h-index

  3. MG
    Martin G. Sanda

    University of Michigan, United States

    1 publications · 54 citations

    1

    h-index

  4. KR
    Katina Robison

    Women & Infants Hospital of Rhode Island, United States

    1 publications · 34 citations

    1

    h-index

  5. AN
    Awadhesh N. Jha

    University of Plymouth, United Kingdom

    1 publications · 119 citations

    1

    h-index

1–5 of 177

Venues

  1. Biometrics

    3 publications · 168 citations

    3

    h-index

  2. Statistics in Medicine

    2 publications · 37 citations

    2

    h-index

  3. Computational Statistics & Data Analysis

    CSDA · 2 publications · 24 citations

    2

    h-index

  4. Environmental Pollution

    1 publications · 24 citations

    1

    h-index

  5. Ecotoxicology and Environmental Safety

    EES · 1 publications · 119 citations

    1

    h-index

1–5