Rule-based Phenotype Classification

Rule-Based Phenotype Classification is a phenotype classification method that relies on predefined diagnostic criteria, clinical guidelines, or expert-derived logical rules to assign phenotype labels to individuals, distinguishing it from data-driven or machine learning approaches by its dependence on explicit, interpretable rules.

10

Publications

240

Citations

108

Authors

42

Institutions

Publications per year

2017–2026

6

Authors

108

  1. CW
    Chunhua Weng

    Columbia University, United States

    2 publications · 42 citations

    2

    h-index

  2. NS
    Ning Shang

    Columbia University, United States

    2 publications · 42 citations

    2

    h-index

  3. NW
    Nephi Walton

    Intermountain Healthcare, United States

    2 publications · 42 citations

    2

    h-index

  4. WW
    Wei‐Qi Wei

    Vanderbilt University Medical Center, United States

    2 publications · 42 citations

    2

    h-index

  5. CL
    Cong Liu

    Columbia University, United States

    2 publications · 42 citations

    2

    h-index

1–5 of 108

Venues

  1. Diabetes Spectrum

    1 publications · 12 citations

    1

    h-index

  2. BioMed Research International

    1 publications · 19 citations

    1

    h-index

  3. Pharmacopsychiatry

    1 publications · 28 citations

    1

    h-index

  4. Brain and Cognition

    1 publications · 19 citations

    1

    h-index

  5. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 1 publications · 10 citations

    1

    h-index

1–5