Machine Learning-based Normalization

Machine Learning-Based Normalization is a computational approach within biomedical concept normalization that employs machine learning algorithms to map heterogeneous biomedical mentions to standardized entries in a reference ontology by learning contextual and semantic representations from data.

62

Publications

3.5K

Citations

193

Authors

87

Institutions

Publications per year

2017–2026

38

Authors

193

  1. ZL
    Zhiyong Lu

    National Center for Biotechnology Information, United States

    8 publications · 885 citations

    8

    h-index

  2. RL
    Robert Leaman

    National Center for Biotechnology Information, United States

    6 publications · 799 citations

    6

    h-index

  3. CW
    Chih-Hsuan Wei

    National Center for Biotechnology Information, United States

    4 publications · 149 citations

    4

    h-index

  4. SJ
    Siddhartha Jonnalagadda

    Northwestern University, United States

    3 publications · 64 citations

    3

    h-index

  5. ZM
    Zulfat Miftahutdinov

    Kazan Federal University, Russia

    2 publications · 130 citations

    2

    h-index

1–5 of 193

Venues

  1. Bioinformatics

    5 publications · 616 citations

    5

    h-index

  2. arXiv (Cornell University)

    Repository · 4 publications · 102 citations

    4

    h-index

  3. Journal of Biomedical Informatics

    3 publications · 308 citations

    3

    h-index

  4. Journal of the American Medical Informatics Association

    JAMIA · 2 publications · 53 citations

    2

    h-index

  5. Database

    2 publications · 45 citations

    2

    h-index

1–5