Semantic Search for Large Scale Clinical Ontologies

• URL: http://arxiv.org/abs/2201.00118v1
• Date: Sat, 1 Jan 2022 05:15:42 GMT
• Title: Semantic Search for Large Scale Clinical Ontologies
• Authors: Duy-Hoa Ngo, Madonna Kemp, Donna Truran, Bevan Koopman, Alejandro Metke-Jimenez
• Abstract summary: We present a deep learning approach to build a search system for large clinical vocabularies. We propose a Triplet-BERT model and a method that generates training data based on semantic training data. The model is evaluated using five real benchmark data sets and the results show that our approach achieves high results on both free text to concept and concept to searching concept vocabularies.
• Score: 63.71950996116403
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Finding concepts in large clinical ontologies can be challenging when queries use different vocabularies. A search algorithm that overcomes this problem is useful in applications such as concept normalisation and ontology matching, where concepts can be referred to in different ways, using different synonyms. In this paper, we present a deep learning based approach to build a semantic search system for large clinical ontologies. We propose a Triplet-BERT model and a method that generates training data directly from the ontologies. The model is evaluated using five real benchmark data sets and the results show that our approach achieves high results on both free text to concept and concept to concept searching tasks, and outperforms all baseline methods.

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