Concepedia

Rule-based Phenotype Identification

Rule-Based Phenotype Identification is a methodological approach in clinical and biomedical informatics that uses predefined logic rules derived from clinical criteria, diagnostic codes, and laboratory data to identify patient cohorts with specific phenotypic characteristics from electronic health records.

18

Publications

1.3K

Citations

179

Authors

67

Institutions

Publications per year

2017–2026

16

Parents

Publications

18

UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER

Spiros Denaxas, Arturo González-Izquierdo, Kenan Direk et al. · Journal of the American Medical Informatics Association · 2019 · 254 citations · Full text

, , +17

Software Application Profile: PHESANT: a tool for performing automated phenome scans in UK Biobank

Louise A C Millard, Neil M Davies, Tom R. Gaunt et al. · International Journal of Epidemiology · 2017 · 248 citations · Full text

, , +13

Advances in Electronic Phenotyping: From Rule-Based Definitions to Machine Learning Models

Juan M. Banda, Martin Seneviratne, Tina Hernandez‐Boussard et al. · Annual Review of Biomedical Data Science · 2018 · 240 citations · Full text

, , +15

Identifying lupus patients in electronic health records: Development and validation of machine learning algorithms and application of rule-based algorithms

April Jorge, Víctor M. Castro, April Barnado et al. · Seminars in Arthritis and Rheumatism · 2019 · 85 citations · Full text

, , +16

Medical records-based chronic kidney disease phenotype for clinical care and “big data” observational and genetic studies

Ning Shang, Atlas Khan, Fernanda Polubriaginof et al. · npj Digital Medicine · 2021 · 75 citations · Full text

, , +17

1–5 of 18

Authors

179

  1. JC
    Joshua C. Denny

    Vanderbilt University, United States

    4 publications · 271 citations

    4

    h-index

  2. NM
    Neil M Davies

    University of Bristol, United Kingdom

    2 publications · 268 citations

    2

    h-index

  3. EW
    Elizabeth W. Karlson

    Brigham and Women's Hospital, United States

    2 publications · 160 citations

    2

    h-index

  4. VS
    Vivian S. Gainer

    Mass General Brigham, United States

    2 publications · 160 citations

    2

    h-index

  5. LA
    Louise A C Millard

    University of Bristol, United Kingdom

    2 publications · 268 citations

    2

    h-index

1–5 of 179

Institutions

67

  1. Mayo Clinic

    Rochester, United States

    3 h-index

    3 publications

    137 citations

  2. University of Pennsylvania

    Philadelphia, United States

    3 h-index

    12 publications

    396 citations

  3. Harvard University

    Cambridge, United States

    3 h-index

    11 publications

    855 citations

  4. Vanderbilt University Medical Center

    Nashville, United States

    3 h-index

    13 publications

    847 citations

  5. Brigham and Women's Hospital

    Boston, United States

    2 h-index

    8 publications

    610 citations

  6. Boston University

    Boston, United States

    2 h-index

    5 publications

    130 citations

  7. Mayo Clinic in Arizona

    Scottsdale, United States

    2 h-index

    6 publications

    270 citations

  8. University of Bristol

    Bristol, United Kingdom

    2 h-index

    6 publications

    348 citations

1–8 of 67

Venues

  1. Annual Review of Biomedical Data Science

    2 publications · 288 citations

    2

    h-index

  2. Statistics in Medicine

    1 publications · 25 citations

    1

    h-index

  3. International Journal of Epidemiology

    1 publications · 248 citations

    1

    h-index

  4. 1

    h-index

  5. Neurology and Therapy

    1 publications · 10 citations

    1

    h-index

1–5