Knowledge-based Signal Detection

Knowledge-Based Signal Detection is a systematic method for identifying potential adverse drug reactions by leveraging predefined biomedical knowledge, such as drug and disease ontologies or established pharmacological relationships, to distinguish meaningful safety signals from background noise in clinical or observational data.

27

Publications

1.1K

Citations

100

Authors

50

Institutions

Publications per year

2017–2026

9

Authors

100

  1. NH
    Nigam H. Shah

    Stanford University, United States

    4 publications · 242 citations

    4

    h-index

  2. RH
    Rave Harpaz

    Stanford University, United States

    3 publications · 226 citations

    3

    h-index

  3. PS
    Peng‐Lang Shui

    Xidian University, China

    2 publications · 30 citations

    2

    h-index

  4. EE
    Elizabeth E. Roughead

    University of South Australia, Australia

    2 publications · 49 citations

    2

    h-index

  5. WD
    William DuMouchel

    Oracle (United States), United States

    2 publications · 214 citations

    2

    h-index

1–5 of 100

Venues

  1. Artificial Intelligence in Medicine

    AIM · 2 publications · 26 citations

    2

    h-index

  2. Journal of Biomedical Informatics

    2 publications · 67 citations

    2

    h-index

  3. Digital Signal Processing

    1 publications · 14 citations

    1

    h-index

  4. Journal of the American Medical Informatics Association

    JAMIA · 1 publications · 175 citations

    1

    h-index

  5. PubMed

    Repository · 1 publications · 12 citations

    1

    h-index

1–5