Unsupervised Phenotype Discovery
Unsupervised Phenotype Discovery is a computational method within the domain of computational phenotyping that identifies novel, data-driven patient subgroups from unlabeled electronic health records through pattern recognition without prior clinical labels or supervision.
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Publications
11.1K
Citations
1.7K
Authors
540
Institutions
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2017–2026
118
Parents
Children
Clinical Embedding LearningCluster Validation In PhenotypingCross-dataset Phenotype ReplicationFeature Extraction For PhenotypingGraph-based Phenotype DiscoveryLatent Phenotype DiscoveryLongitudinal Phenotype DiscoveryMulti-modal Phenotype DiscoveryOntology-free PhenotypingPatient Similarity Modeling
138
Identifying facial phenotypes of genetic disorders using deep learning
Yaron Gurovich, Yair Hanani, Omri Bar et al. · Nature Medicine · 2018 · 732 citations
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Harvard University
Cambridge, United States
8 h-index
21 publications
2.1K citations
Inserm
Paris, France
7 h-index
38 publications
1.4K citations

University of Toronto
Toronto, Canada
7 h-index
20 publications
1.3K citations
University of Pittsburgh
Pittsburgh, United States
7 h-index
42 publications
26.8K citations
Mayo Clinic
Rochester, United States
6 h-index
13 publications
420 citations
University of Oxford
Oxford, United Kingdom
6 h-index
20 publications
482 citations
Stanford University
Stanford, United States
6 h-index
34 publications
5.5K citations

Brigham and Women's Hospital
Boston, United States
6 h-index
10 publications
1.6K citations
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6 publications · 141 citations
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4 publications · 289 citations
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4 publications · 168 citations
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Repository · 2 publications · 59 citations
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AJRCCM · 3 publications · 2.3K citations
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