Clinical Text Summarization

Clinical Text Summarization is a computational method within Clinical Natural Language Processing that generates concise, accurate, and clinically relevant summaries from electronic health records or other clinical documents by identifying and preserving essential medical information while omitting redundant or non-essential content.

210

Publications

13.5K

Citations

883

Authors

355

Institutions

Publications per year

2017–2026

112

Authors

883

  1. ER
    Ehud Reiter

    University of Aberdeen, United Kingdom

    8 publications · 581 citations

    8

    h-index

  2. HL
    Hongfang Liu

    Mayo Clinic in Florida, United States

    7 publications · 198 citations

    7

    h-index

  3. NE
    Noémie Elhadad

    Columbia University, United States

    6 publications · 306 citations

    6

    h-index

  4. SS
    Somayajulu Sripada

    University of Aberdeen, United Kingdom

    5 publications · 514 citations

    5

    h-index

  5. MF
    Marcelo Fiszman

    United States National Library of Medicine, United States

    5 publications · 222 citations

    5

    h-index

1–5 of 883

Venues

  1. PubMed

    Repository · 27 publications · 1.1K citations

    19

    h-index

  2. Journal of the American Medical Informatics Association

    JAMIA · 16 publications · 1.1K citations

    15

    h-index

  3. Journal of Biomedical Informatics

    14 publications · 2K citations

    13

    h-index

  4. arXiv (Cornell University)

    Repository · 11 publications · 1K citations

    10

    h-index

  5. BMC Medical Informatics and Decision Making

    5 publications · 248 citations

    5

    h-index

1–5