Algorithmic Phenotyping Evaluation

Algorithmic Phenotyping Evaluation is a scholarly methodological framework that systematically assesses the accuracy, reliability, and generalizability of computational algorithms designed to derive phenotypic definitions from complex biomedical data.

3

Publications

99

Citations

17

Authors

7

Institutions

Publications per year

2017–2026

3

Authors

17

  1. JS
    Ju Sun

    University of Minnesota, United States

    1 publications · 18 citations

    1

    h-index

  2. SZ
    Sicheng Zhou

    University of Minnesota, United States

    1 publications · 18 citations

    1

    h-index

  3. KK
    Karin Kopitowski

    Hospital Italiano de Buenos Aires, Argentina

    1 publications · 26 citations

    1

    h-index

  4. RZ
    Rui Zhang

    University of Minnesota, United States

    1 publications · 18 citations

    1

    h-index

  5. HL
    Hongfang Liu

    Mayo Clinic in Florida, United States

    1 publications · 18 citations

    1

    h-index

1–5 of 17

Venues

  1. 1

    h-index

  2. Computer Methods and Programs in Biomedicine

    1 publications · 26 citations

    1

    h-index

  3. Journal of Biomedical Informatics

    1 publications · 55 citations

    1

    h-index

  4. Journal of Medical Internet Research

    1 publications · 12 citations

1–4