Free-text Mining
Free-Text Mining is a computational methodology within the domain of public health surveillance that involves the systematic extraction and analysis of unstructured textual data from clinical or epidemiological records to identify and characterize Influenza-Like Illness indicators, distinguishing it from structured data analysis by its focus on natural language patterns and context-dependent symptom representation.
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Publications
17.8K
Citations
1.4K
Authors
483
Institutions
Publications per year
2017–2026
130
328
RelEx—Relation extraction using dependency parse trees
Katrin Fundel, Robert Küffner, Ralf Zimmer · Bioinformatics · 2006 · 569 citations · Full text
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483
Harvard University
Cambridge, United States
11 h-index
54 publications
3.4K citations
Stanford University
Stanford, United States
11 h-index
36 publications
3.4K citations
King's College London
London, United Kingdom
9 h-index
32 publications
1.9K citations

Brigham and Women's Hospital
Boston, United States
9 h-index
49 publications
1.6K citations
University of Utah
Salt Lake City, United States
9 h-index
38 publications
1.3K citations

Imperial College London
London, United Kingdom
7 h-index
18 publications
2.2K citations
University of Pennsylvania
Philadelphia, United States
7 h-index
12 publications
1.2K citations
University College London
London, United Kingdom
7 h-index
32 publications
1.1K citations
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Repository · 26 publications · 817 citations
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11 publications · 315 citations
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6 publications · 594 citations
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JAMIA · 6 publications · 398 citations
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5 publications · 311 citations
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