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Towards Transforming Expert-based Content to Evidence-based Content

The goal of this paper is to find relevant citations for clinicians’ written content and make it more reliable by adding scientific articles as references and enabling the clinicians to easily update it using new information. The proposed approach uses information retrieval and ranking techniques to...

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Detalles Bibliográficos
Autores principales: Moosavinasab, Soheil, Rastegar-Mojarad, Majid, Liu, Hongfang, Jonnalagadda, Siddhartha R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419763/
https://www.ncbi.nlm.nih.gov/pubmed/25954582
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author Moosavinasab, Soheil
Rastegar-Mojarad, Majid
Liu, Hongfang
Jonnalagadda, Siddhartha R.
author_facet Moosavinasab, Soheil
Rastegar-Mojarad, Majid
Liu, Hongfang
Jonnalagadda, Siddhartha R.
author_sort Moosavinasab, Soheil
collection PubMed
description The goal of this paper is to find relevant citations for clinicians’ written content and make it more reliable by adding scientific articles as references and enabling the clinicians to easily update it using new information. The proposed approach uses information retrieval and ranking techniques to extract and rank relevant citations from MEDLINE for any given sentence. Additionally, this system extracts snippets of relevant content from ranked citations. We assessed our approach on 4,697 MEDLINE papers and their corresponding full-text on the subject of Heart Failure. We implemented multi-level and weight ranking algorithms to rank the citations. We demonstrate that using journal relevance and study design type improves results obtained from only using content similarity by approximately 40%. We also show that using full-text, rather than abstract text, leads to extracting higher quality snippets.
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spelling pubmed-44197632015-05-07 Towards Transforming Expert-based Content to Evidence-based Content Moosavinasab, Soheil Rastegar-Mojarad, Majid Liu, Hongfang Jonnalagadda, Siddhartha R. AMIA Jt Summits Transl Sci Proc Articles The goal of this paper is to find relevant citations for clinicians’ written content and make it more reliable by adding scientific articles as references and enabling the clinicians to easily update it using new information. The proposed approach uses information retrieval and ranking techniques to extract and rank relevant citations from MEDLINE for any given sentence. Additionally, this system extracts snippets of relevant content from ranked citations. We assessed our approach on 4,697 MEDLINE papers and their corresponding full-text on the subject of Heart Failure. We implemented multi-level and weight ranking algorithms to rank the citations. We demonstrate that using journal relevance and study design type improves results obtained from only using content similarity by approximately 40%. We also show that using full-text, rather than abstract text, leads to extracting higher quality snippets. American Medical Informatics Association 2014-04-07 /pmc/articles/PMC4419763/ /pubmed/25954582 Text en ©2014 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
spellingShingle Articles
Moosavinasab, Soheil
Rastegar-Mojarad, Majid
Liu, Hongfang
Jonnalagadda, Siddhartha R.
Towards Transforming Expert-based Content to Evidence-based Content
title Towards Transforming Expert-based Content to Evidence-based Content
title_full Towards Transforming Expert-based Content to Evidence-based Content
title_fullStr Towards Transforming Expert-based Content to Evidence-based Content
title_full_unstemmed Towards Transforming Expert-based Content to Evidence-based Content
title_short Towards Transforming Expert-based Content to Evidence-based Content
title_sort towards transforming expert-based content to evidence-based content
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419763/
https://www.ncbi.nlm.nih.gov/pubmed/25954582
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