Clinical Embedding Learning
Clinical Embedding Learning is a computational methodology in unsupervised phenotype discovery that maps clinical data into low-dimensional vector representations to preserve semantic relationships and facilitate the identification of latent patient subgroups.
42
Publications
3.3K
Citations
189
Authors
90
Institutions
Publications per year
2017–2026
39
42
Publicly Available Clinical BERT Embeddings
Emily Alsentzer, John R. Murphy, Willie Boag et al. · arXiv (Cornell University) · 2019 · 726 citations · Full text
Measuring Patient Similarities via a Deep Architecture with Medical Concept Embedding
Zihao Zhu, Changchang Yin, Buyue Qian et al. · 2016 · 125 citations
Haoran Zhang, Amy X. Lu, Mohamed Abdalla et al. · 2020 · 122 citations
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The University of Texas Health Science Center at Houston
Houston, United States
4 h-index
20 publications
3.9K citations
Vector Institute
Toronto, Canada
2 h-index
6 publications
526 citations

Beijing University of Technology
Beijing, China
2 h-index
4 publications
188 citations
Northwestern University
Evanston, United States
2 h-index
10 publications
390 citations

University of Toronto
Toronto, Canada
2 h-index
6 publications
526 citations

The University of Sydney
Sydney, Australia
2 h-index
7 publications
190 citations
University of Pennsylvania
Philadelphia, United States
2 h-index
5 publications
269 citations
University of California, San Francisco
San Francisco, United States
2 h-index
9 publications
360 citations
1–8 of 90
Repository · 4 publications · 788 citations
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3 publications · 65 citations
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3 publications · 198 citations
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2 publications · 91 citations
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1 publications · 16 citations
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