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|Title:||A Semantic Multi-Field Clinical Search for Patient Medical Records||Authors:||Umamaheswari Vasanthakumar, E.
Application to NLP
|Issue Date:||2018||Source:||Umamaheswari Vasanthakumar, E., & Bond, F. (2018). A Semantic Multi-Field Clinical Search for Patient Medical Records. Cybernetics and Information Technologies, 18(1), 171-182.||Series/Report no.:||Cybernetics and Information Technologies||Abstract:||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.||URI:||https://hdl.handle.net/10356/88458
|ISSN:||1311-9702||Rights:||© 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.||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||HSS Journal Articles|
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Updated on Feb 28, 2021
Updated on Feb 28, 2021
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