Automatic Phenotyping

Automatic Phenotyping is a computational method in clinical natural language processing that identifies and classifies patient-specific clinical characteristics from unstructured electronic health records by leveraging textual data to infer phenotypic profiles.

101

Publications

5.5K

Citations

598

Authors

206

Institutions

Publications per year

2017–2026

75

Variants

Automated Phenotyping

Authors

598

  1. JC
    Joshua C. Denny

    Vanderbilt University, United States

    9 publications · 699 citations

    9

    h-index

  2. JP
    Jyotishman Pathak

    Cornell University, United States

    8 publications · 531 citations

    8

    h-index

  3. HL
    Hongfang Liu

    Mayo Clinic in Florida, United States

    7 publications · 303 citations

    7

    h-index

  4. VS
    Vivian S. Gainer

    Mass General Brigham, United States

    5 publications · 518 citations

    5

    h-index

  5. AK
    Abel Kho

    Northwestern University, United States

    5 publications · 393 citations

    5

    h-index

1–5 of 598

Venues

  1. Journal of the American Medical Informatics Association

    JAMIA · 12 publications · 1.1K citations

    12

    h-index

  2. PubMed

    Repository · 9 publications · 439 citations

    9

    h-index

  3. Journal of Biomedical Informatics

    8 publications · 311 citations

    8

    h-index

  4. Studies in health technology and informatics

    Book series · 5 publications · 131 citations

    5

    h-index

  5. Plant Methods

    4 publications · 467 citations

    4

    h-index

1–5