A Semantic Multi-Field Clinical Search for Patient Medical Records

A semantic-based search engine for clinical data would be a substantial aid for hospitals to provide support for clinical practitioners. Since electronic medical records of patients contain a variety of information, there is a need to extract meaningful patterns from the Patient Medical Records (PMR...

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Main Authors:	Umamaheswari Vasanthakumar, E., Bond, Francis
其他作者:	School of Humanities and Social Sciences
格式:	Article
語言:	English
出版:	2018
主題:	Semantic Similarity Application to NLP
在線閱讀:	https://hdl.handle.net/10356/88458 http://hdl.handle.net/10220/44637 http://www.cit.iit.bas.bg/CIT_2018/v-18-1/14_paper.pdf
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機構:	Nanyang Technological University
語言:	English

id	sg-ntu-dr.10356-88458
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spelling	sg-ntu-dr.10356-884582019-12-06T17:03:46Z A Semantic Multi-Field Clinical Search for Patient Medical Records Umamaheswari Vasanthakumar, E. Bond, Francis School of Humanities and Social Sciences Semantic Similarity Application to NLP A semantic-based search engine for clinical data would be a substantial aid for hospitals to provide support for clinical practitioners. Since electronic medical records of patients contain a variety of information, there is a need to extract meaningful patterns from the Patient Medical Records (PMR). The proposed work matches patients to relevant clinical practice guidelines (CPGs) by matching their medical records with the CPGs. However in both PMR and CPG, the information pertaining to symptoms, diseases, diagnosis procedures and medicines is not structured and there is a need to pre-process and index the information in a meaningful way. In order to reduce manual effort to match to the clinical guidelines, this work automatically extracts the clinical guidelines from the PDF documents using a set of regular expression rules and indexes them with a multi-field index using Lucene. We have attempted a multi-field Lucene search and ontology-based advanced search, where the PMR is mapped to SNOMED core subset to find the important concepts. We found that the ontology-based search engine gave more meaningful results for specific queries when compared to term based search. Published version 2018-04-04T03:02:39Z 2019-12-06T17:03:46Z 2018-04-04T03:02:39Z 2019-12-06T17:03:46Z 2018 2018 Journal Article Umamaheswari Vasanthakumar, E., & Bond, F. (2018). A Semantic Multi-Field Clinical Search for Patient Medical Records. Cybernetics and Information Technologies, 18(1), 171-182. 1311-9702 https://hdl.handle.net/10356/88458 http://hdl.handle.net/10220/44637 http://www.cit.iit.bas.bg/CIT_2018/v-18-1/14_paper.pdf 204339 en Cybernetics and Information Technologies © 2018 The author(s). This paper was published in Cybernetics and Information Technologies and is made available as an electronic reprint (preprint) with permission of Institute of Information and Communication Technologies. The published version is available at: [http://www.cit.iit.bas.bg/CIT_2018/v-18-1/14_paper.pdf]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 12 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
country	Singapore
collection	DR-NTU
language	English
topic	Semantic Similarity Application to NLP
spellingShingle	Semantic Similarity Application to NLP Umamaheswari Vasanthakumar, E. Bond, Francis A Semantic Multi-Field Clinical Search for Patient Medical Records
description	A semantic-based search engine for clinical data would be a substantial aid for hospitals to provide support for clinical practitioners. Since electronic medical records of patients contain a variety of information, there is a need to extract meaningful patterns from the Patient Medical Records (PMR). The proposed work matches patients to relevant clinical practice guidelines (CPGs) by matching their medical records with the CPGs. However in both PMR and CPG, the information pertaining to symptoms, diseases, diagnosis procedures and medicines is not structured and there is a need to pre-process and index the information in a meaningful way. In order to reduce manual effort to match to the clinical guidelines, this work automatically extracts the clinical guidelines from the PDF documents using a set of regular expression rules and indexes them with a multi-field index using Lucene. We have attempted a multi-field Lucene search and ontology-based advanced search, where the PMR is mapped to SNOMED core subset to find the important concepts. We found that the ontology-based search engine gave more meaningful results for specific queries when compared to term based search.
author2	School of Humanities and Social Sciences
author_facet	School of Humanities and Social Sciences Umamaheswari Vasanthakumar, E. Bond, Francis
format	Article
author	Umamaheswari Vasanthakumar, E. Bond, Francis
author_sort	Umamaheswari Vasanthakumar, E.
title	A Semantic Multi-Field Clinical Search for Patient Medical Records
title_short	A Semantic Multi-Field Clinical Search for Patient Medical Records
title_full	A Semantic Multi-Field Clinical Search for Patient Medical Records
title_fullStr	A Semantic Multi-Field Clinical Search for Patient Medical Records
title_full_unstemmed	A Semantic Multi-Field Clinical Search for Patient Medical Records
title_sort	semantic multi-field clinical search for patient medical records
publishDate	2018
url	https://hdl.handle.net/10356/88458 http://hdl.handle.net/10220/44637 http://www.cit.iit.bas.bg/CIT_2018/v-18-1/14_paper.pdf
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A Semantic Multi-Field Clinical Search for Patient Medical Records

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