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Building a Specialized Lexicon for Breast Cancer Clinical Trial Subject Eligibility Analysis by Euisung Jung; Hemant Jain; Atish P Sinha; Carmelo Gaudioso is a Health Professions article available to read on EtoBox.

What is Building a Specialized Lexicon for Breast Cancer Clinical Trial Subject Eligibility Analysis about?

A natural language processing (NLP) application requires sophisticated lexical resources to support its processing goals. Different solutions, such as dictionary lookup and MetaMap, have been proposed in the healthcare informatics literature to identify disease terms with more than one word (multi-gram disease named entities). Although a lot of work has been done in the identification of protein-and gene-named entities in the biomedical field, not much research has been done on the recognition and resolution of terminologies in the clinical trial subject eligibility analysis. In this study, we develop a specialized lexicon for improving NLP and text mining analysis in the breast cancer domain, and evaluate it by comparing it with the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). We use a hybrid methodology, which combines the knowledge of domain experts, terms from multiple online dictionaries, and the mining of text from sample clinical trials. Use of our methodology introduces 4243 unique lexicon items, which increase bigram entity match by 38.6% and trigram entity match by 41%. Our lexicon, which adds a significant number of new terms, is very useful for matc

Who reads Building a Specialized Lexicon for Breast Cancer Clinical Trial Subject Eligibility Analysis?

Author

Euisung Jung; Hemant Jain; Atish P Sinha; Carmelo Gaudioso

Publisher

SAGE Publications

Published

2021

Language

EN

Field

Health Professions (Health Sciences)