{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:34:34Z","timestamp":1754156074516,"version":"3.41.2"},"reference-count":50,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2019,8,19]],"date-time":"2019-08-19T00:00:00Z","timestamp":1566172800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJWIS"],"published-print":{"date-parts":[[2019,8,19]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this study is to propose a framework for extracting medical information from the Web using domain ontologies. Patient\u2013Doctor conversations have become prevalent on the Web. For instance, solutions like HealthTap or AskTheDoctors allow patients to ask doctors health-related questions. However, most online health-care consumers still struggle to express their questions efficiently due mainly to the expert\/layman language and knowledge discrepancy. Extracting information from these layman descriptions, which typically lack expert terminology, is challenging. This hinders the efficiency of the underlying applications such as information retrieval. Herein, an ontology-driven approach is proposed, which aims at extracting information from such sparse descriptions using a meta-model.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>A meta-model is designed to bridge the gap between the vocabulary of the medical experts and the consumers of the health services. The meta-model is mapped with SNOMED-CT to access the comprehensive medical vocabulary, as well as with WordNet to improve the coverage of layman terms during information extraction. To assess the potential of the approach, an information extraction prototype based on syntactical patterns is implemented.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The evaluation of the approach on the gold standard corpus defined in Task1 of ShARe CLEF 2013 showed promising results, an <jats:italic>F<\/jats:italic>-score of 0.79 for recognizing medical concepts in real-life medical documents.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The originality of the proposed approach lies in the way information is extracted. The context defined through a meta-model proved to be efficient for the task of information extraction, especially from layman descriptions.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/ijwis-03-2018-0017","type":"journal-article","created":{"date-parts":[[2018,12,11]],"date-time":"2018-12-11T09:06:07Z","timestamp":1544519167000},"page":"359-382","source":"Crossref","is-referenced-by-count":3,"title":["Ontology-based approach to enhance medical web information extraction"],"prefix":"10.1108","volume":"15","author":[{"given":"Nassim Abdeldjallal","family":"Otmani","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Malik","family":"Si-Mohammed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Catherine","family":"Comparot","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pierre-Jean","family":"Charrel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2020092519154518100_ref001","first-page":"817","article-title":"Automatic annotation of medical records","volume":"116","year":"2005","journal-title":"Studies in Health Technology and Informatics"},{"key":"key2020092519154518100_ref002","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.jss.2015.10.041","article-title":"Considering context in the design of intelligent systems: current practices and suggestions for improvement","volume":"112","year":"2016","journal-title":"Journal of Systems and Software"},{"key":"key2020092519154518100_ref003","first-page":"760","article-title":"Semantic AutoSuggest for electronic health records","volume-title":"International Conference on Computational Science and Computational Intelligence (CSCI), Presented at the 2015 International Conference on Computational Science and Computational Intelligence (CSCI)","year":"2015"},{"key":"key2020092519154518100_ref004","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1016\/j.ipm.2015.04.006","article-title":"MEANS: a medical question-answering system combining NLP techniques and semantic web technologies","volume":"51","year":"2015","journal-title":"Information Processing and Management"},{"volume-title":"Electronic Health Records: A Guide for Clinicians and Administrators","year":"2008","key":"key2020092519154518100_ref005"},{"key":"key2020092519154518100_ref006","unstructured":"Consumer Health Vocabulary Initiative (2013), [WWW Document], available at: http:\/\/consumerhealthvocab.org\/ (accessed 13 March 2017)."},{"year":"2014","key":"key2020092519154518100_ref007","article-title":"Annotation of specialized corpora using a comprehensive entity and relation scheme"},{"issue":"7206","key":"key2020092519154518100_ref008","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1136\/bmj.319.7206.358","article-title":"Analysis of questions asked by family doctors regarding patient care","volume":"319","year":"1999","journal-title":"BMJ"},{"key":"key2020092519154518100_ref009","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.ymeth.2015.01.015","article-title":"Application of text mining in the biomedical domain","volume":"74","year":"2015","journal-title":"Methods"},{"volume-title":"Health Online","year":"2013","key":"key2020092519154518100_ref010"},{"key":"key2020092519154518100_ref011","first-page":"310","article-title":"Automatic extraction of layman names for technical medical terms","volume-title":"IEEE International Conference on Healthcare Informatics, Presented at the 2014 IEEE International Conference on Healthcare Informatics","year":"2014"},{"key":"key2020092519154518100_ref011a","first-page":"199","article-title":"A translation approach to portable ontology specifications","volume-title":"Knowledge Acquisition","year":"1993"},{"key":"key2020092519154518100_ref012","first-page":"652","article-title":"Question answering system based on ontology and semantic web","volume-title":"Rough Sets and Knowledge Technology. 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