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
210
Emily Alsentzer, John R. Murphy, William Boag et al. · 2019 · 1.6K citations · Full text
Publicly Available Clinical BERT Embeddings
Emily Alsentzer, John R. Murphy, Willie Boag et al. · arXiv (Cornell University) · 2019 · 726 citations · Full text
Evaluating large language models on medical evidence summarization
Liyan Tang, Zhaoyi Sun, Betina Idnay et al. · npj Digital Medicine · 2023 · 367 citations · Full text
1–5 of 210
883
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United States National Library of Medicine, United States
5 publications · 222 citations
5
h-index
1–5 of 883
355
Columbia University
New York, United States
17 h-index
49 publications
4.7K citations
Harvard University
Cambridge, United States
8 h-index
23 publications
974 citations
Stanford University
Stanford, United States
8 h-index
54 publications
11K citations

University of Aberdeen
Aberdeen, United Kingdom
8 h-index
20 publications
2K citations
National Institutes of Health
Bethesda, United States
7 h-index
19 publications
1.3K citations

Vanderbilt University
Nashville, United States
6 h-index
11 publications
571 citations
University of Utah
Salt Lake City, United States
6 h-index
10 publications
514 citations

United States National Library of Medicine
Bethesda, United States
6 h-index
15 publications
1.1K citations
1–8 of 355
Repository · 27 publications · 1.1K citations
19
h-index
JAMIA · 16 publications · 1.1K citations
15
h-index
14 publications · 2K citations
13
h-index
Repository · 11 publications · 1K citations
10
h-index
5 publications · 248 citations
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