Cross-dataset Phenotype Replication

Cross-Dataset Phenotype Replication is a validation framework in unsupervised phenotype discovery that assesses the consistency and generalizability of derived phenotypes across distinct, independently collected datasets by systematically evaluating their structural and clinical coherence beyond the original derivation cohort.

5

Publications

661

Citations

37

Authors

15

Institutions

Publications per year

2017–2026

4

Authors

37

  1. JL
    Jonathan L. Haines

    University of Miami, United States

    1 publications · 330 citations

    1

    h-index

  2. ME
    Micaela Elisa Consens

    University of Toronto, Canada

    1 publications · 18 citations

    1

    h-index

  3. GM
    Gladston Moreira

    Universidade Federal de Ouro Preto, Brazil

    1 publications · 240 citations

    1

    h-index

  4. ML
    Malte Lorbach

    Utrecht University, Netherlands

    1 publications · 51 citations

    1

    h-index

  5. AW
    Aleksander Wawer

    Institute of Computer Science, Poland

    1 publications · 22 citations

    1

    h-index

1–5 of 37

Venues

  1. Cognitive Computation

    1 publications · 22 citations

    1

    h-index

  2. Neurobiology of Aging

    1 publications · 18 citations

    1

    h-index

  3. Journal of Neuroscience Methods

    1 publications · 51 citations

    1

    h-index

  4. Informatics in Medicine Unlocked

    IMU · 1 publications · 240 citations

    1

    h-index

  5. The American Journal of Human Genetics

    AJHG · 1 publications · 330 citations

    1

    h-index

1–5