UMLS::Similarity: Measuring the Relatedness and Similarity of Biomedical Concepts
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Semantic Textual SimilaritySimilar Papers 제목 키워드 기반
Retrofitting Concept Vector Representations of Medical Concepts to Improve Estimates of Semantic Similarity and Relatedness
Estimation of semantic similarity and relatedness between biomedical concepts has utility for many informatics applications. Automated methods fall into two categories: methods based on distributional statistics drawn fr…
Semantic SimilaritySemantic Textual SimilarityThe MeSH-gram Neural Network Model: Extending Word Embedding Vectors with MeSH Concepts for UMLS Semantic Similarity and Relatedness in the Biomedical Domain
Eliciting semantic similarity between concepts in the biomedical domain remains a challenging task. Recent approaches founded on embedding vectors have gained in popularity as they risen to efficiently capture semantic r…
Semantic SimilaritySemantic Textual SimilarityUBERT: A Novel Language Model for Synonymy Prediction at Scale in the UMLS Metathesaurus
The UMLS Metathesaurus integrates more than 200 biomedical source vocabularies. During the Metathesaurus construction process, synonymous terms are clustered into concepts by human editors, assisted by lexical similarity…
Language ModelingLanguage ModellingPredictionSentenceUBERT: A Novel Language Model for Synonymy Prediction at Scale in the UMLS Metathesaurus
The UMLS Metathesaurus integrates more than 200 biomedical source vocabularies. During the Metathesaurus construction process, synonymous terms are clustered into concepts by human editors, assisted by lexical similarity…
Language ModelingLanguage ModellingPredictionSentenceA Hybrid Approach to Measure Semantic Relatedness in Biomedical Concepts
Objective: This work aimed to demonstrate the effectiveness of a hybrid approach based on Sentence BERT model and retrofitting algorithm to compute relatedness between any two biomedical concepts. Materials and Methods: …
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