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Enriching representation learning using 53 million patient notes through human phenotype ontology embedding

Maryam Daniali, Peter D. Galer, David Lewis‐Smith, Shridhar Parthasarathy, Edward Kim, Dario D. Salvucci, Jeffrey M. Miller, Scott Haag, Ingo Helbig

2023Artificial Intelligence in Medicine25 citationsDOIOpen Access PDF

Topics & Concepts

EmbeddingPhenotypeComputer scienceOntologyRepresentation (politics)Similarity (geometry)Artificial intelligenceClinical phenotypeMachine learningFeature learningSemantic similarityComputational biologyBiologyGeneGeneticsPoliticsEpistemologyLawPolitical sciencePhilosophyImage (mathematics)Biomedical Text Mining and OntologiesMachine Learning in HealthcareBioinformatics and Genomic Networks
Enriching representation learning using 53 million patient notes through human phenotype ontology embedding | Litcius