Biomedical Text Mining

Biomedical text mining is a subfield of text mining that applies natural language processing and computational methods to the automated extraction and normalization of biological and medical information from biomedical literature and documents.

5.4K

Publications

290.5K

Citations

16.1K

Authors

3.3K

Institutions

Publications per year

2017–2026

2.5K

Authors

16.1K

  1. ZL
    Zhiyong Lu

    National Center for Biotechnology Information, United States

    101 publications · 12.1K citations

    54

    h-index

  2. SA
    Sophia Ananiadou

    University of Manchester, United Kingdom

    76 publications · 3.9K citations

    37

    h-index

  3. HX
    Hua Xu

    The University of Texas Health Science Center at Houston, United States

    63 publications · 3.8K citations

    34

    h-index

  4. JT
    Jun’ichi Tsujii

    The University of Tokyo, Japan

    55 publications · 4.6K citations

    33

    h-index

  5. ZY
    Zhihao Yang

    Dalian University of Technology, China

    52 publications · 3.3K citations

    30

    h-index

1–5 of 16.1K

Venues

  1. Bioinformatics

    230 publications · 29.7K citations

    87

    h-index

  2. BMC Bioinformatics

    318 publications · 20.1K citations

    74

    h-index

  3. Journal of the American Medical Informatics Association

    JAMIA · 183 publications · 14.6K citations

    64

    h-index

  4. Journal of Biomedical Informatics

    266 publications · 17.2K citations

    64

    h-index

  5. PubMed

    Repository · 287 publications · 11.7K citations

    54

    h-index

1–5

See also

Biomedical Text Mining

Core Methods

Applications

Evaluation

Limitations