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Towards Creating an Iso-semantic Lexicon Model using Computational Semantics and Sublanguage Analysis Within Clinical Subdomains for Medical Language Processing

In Doctoral Consortium - DCBIOSTEC, 42-51, 2015, Lisbon, Portugal

Authors: B. S. Begum Durgahee and Adi Gundlapalli

Affiliation: University of Utah and VA Salt Lake Health Care System, United States

Keyword(s): Information Extraction, Natural Language Processing, Semantic Lexicons, Ontology-based lexicons.

Abstract: Although the widespread adoptions of Electronic Health Records (EHR) have made clinical data available in electronic format, a significant amount of important information is represented in unstructured narrative (free text) form. This complicates the use of these clinical data for decision support and research. Recent efforts have been aimed at applying natural language processing (NLP) and information extraction (IE) techniques to clinical text. A common practice is to manually construct semantic lexicons and use those to identify and extract clinical entities for specific tasks such as cohort identification and phenotyping. Besides requiring intensive manual, linguistic and medical knowledge, the vocabulary tends to be restricted to specific institutions and groups of users. There is no standardized way of building lexicons and this impedes the performance of the NLP or IE, due to inconsistent word usage. The objective of the proposed research study is to find a method of leveraging semantic lexicons to enable sharing of lexicons for information extraction from clinical text. Current NLP tools are mostly focused on clinical entity extraction by mapping textual elements to available ontologies. This method is insufficient due to ontology incompleteness and context dependent entities. Hence, there is a need for deeper understanding of relations among these entities in order to expand existing dictionaries accordingly. Lexico-semantic relations and patterns from heterogeneous clinical text will be detected in terms of sublanguage specific patterns. The discovered significant relations and patterns will be used with unsupervised methods, formal concept analysis, distributive analysis techniques and existing ontologies to inform the design of a learning-based system for automatic construction of clinical ontology-based lexicons. The Semantic Web technologies will be investigated to build a common ontology-based lexicons, using ontological and lexical representations. The ultimate goal of using Semantic Web technologies will be to interlink lexical resources with Biomedical ontologies in a computable form for sharing. This research proposal will contribute to the discovery of new concepts and relations in the clinical domain of interest. While automating the ontology-based lexicon construction with minimal supervised learning, we intend to enhance word sense and improve the text processing to retrieve accurate results. The resulting ontology-based semantic lexicon model will provide a new perspective towards standardizing semantic lexicons to facilitate content interoperability for clinical text mining and natural language processing tasks. Such a model will be helpful in predictive modeling studies for personalized healthcare to provide better health care with more efficient use of limited resources. (More)

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Paper citation in several formats:
Durgahee, B. and Gundlapalli, A. (2015). Towards Creating an Iso-semantic Lexicon Model using Computational Semantics and Sublanguage Analysis Within Clinical Subdomains for Medical Language Processing.In Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2015) ISBN , pages 42-51

@conference{dcbiostec15,
author={B. S. Begum Durgahee. and Adi Gundlapalli.},
title={Towards Creating an Iso-semantic Lexicon Model using Computational Semantics and Sublanguage Analysis Within Clinical Subdomains for Medical Language Processing},
booktitle={Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2015)},
year={2015},
pages={42-51},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={},
}

TY - CONF

JO - Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2015)
TI - Towards Creating an Iso-semantic Lexicon Model using Computational Semantics and Sublanguage Analysis Within Clinical Subdomains for Medical Language Processing
SN -
AU - Durgahee, B.
AU - Gundlapalli, A.
PY - 2015
SP - 42
EP - 51
DO -

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