Machine Learning Case Identification

Machine Learning Case Identification is a computational methodology within passive case finding that employs machine learning algorithms to automatically detect and classify potential cases of interest from unstructured or large-scale data sources based on learned patterns and features.

15

Publications

719

Citations

74

Authors

29

Institutions

Publications per year

2017–2026

10

Authors

74

  1. TK
    Tsung-Ting Kuo

    University of California San Diego, United States

    1 publications · 70 citations

    1

    h-index

  2. JW
    Jochen Walker

    Institute for Applied Economic Research, Germany

    1 publications · 27 citations

    1

    h-index

  3. AN
    Arya Nick Shamie

    University of California, Los Angeles, United States

    1 publications · 23 citations

    1

    h-index

  4. RL
    Rebeccah L. Sokol

    University of Michigan, United States

    1 publications · 50 citations

    1

    h-index

  5. MS
    Marie Schild

    Pfizer (Germany), Germany

    1 publications · 27 citations

    1

    h-index

1–5 of 74

Venues

  1. Journal of the Society for Social Work and Research

    JSSWR · 1 publications · 50 citations

    1

    h-index

  2. Social Science Computer Review

    SSCR · 1 publications · 35 citations

    1

    h-index

  3. Journal Of Big Data

    1 publications · 76 citations

    1

    h-index

  4. JAMA Network Open

    1 publications · 166 citations

    1

    h-index

  5. JAMA Cardiology

    1 publications · 110 citations

    1

    h-index

1–5