Platform Bias Correction

Platform Bias Correction is a methodological framework within cross-platform data harmonization that systematically identifies and mitigates systematic distortions arising from platform-specific technical, operational, or sampling differences to ensure equitable representation and comparability of data across heterogeneous digital environments.

9

Publications

2K

Citations

69

Authors

45

Institutions

Publications per year

2017–2026

6

Authors

69

  1. HK
    Helena Kuivaniemi

    Wayne State University, United States

    1 publications · 17 citations

    1

    h-index

  2. CL
    Cristian-Daniel Llach

    Universitat de Barcelona, Spain

    1 publications · 24 citations

    1

    h-index

  3. AS
    Aleix Solanes

    Consorci Institut D'Investigacions Biomediques August Pi I Sunyer, Spain

    1 publications · 24 citations

    1

    h-index

  4. AB
    Anton Buzdin

    Institute of Bioorganic Chemistry, Russia

    1 publications · 70 citations

    1

    h-index

  5. OK
    Olga Kovalchuk

    University of Lethbridge, Canada

    1 publications · 70 citations

    1

    h-index

1–5 of 69

Venues

  1. Behavior Research Methods

    BRM · 1 publications · 1.6K citations

    1

    h-index

  2. BMC Medical Genomics

    1 publications · 54 citations

    1

    h-index

  3. Bioinformatics

    1 publications · 124 citations

    1

    h-index

  4. Frontiers in Genetics

    1 publications · 17 citations

    1

    h-index

  5. PLoS Computational Biology

    1 publications · 25 citations

    1

    h-index

1–5