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Title: Knowledge Retrieval from PubMed Abstracts and Electronic Medical Records with the Multiple Sclerosis Ontology
Author: Malhotra, Ashutosh
Gündel, Michaela
Rajput, Abdul Mateen
Mevissen, Heinz-Theodor
Saiz Hinajeros, Albert
Pastor Durán, Xavier
Lozano Rubí, Raimundo
Martinez Lapsicina, Elena H.
Zubizarreta, Irati
Mueller, Bernd
Kotelnikova, Ekaterina
Toldo, Luca
Hofmann Apitius, Martin
Villoslada, Pablo
Keywords: MEDLINE
Recursos electrònics en xarxa
Esclerosi múltiple
Informació científica i tècnica
Computer network resources
Multiple sclerosis
Science and technical information
Issue Date: 9-Feb-2015
Publisher: Public Library of Science (PLoS)
Abstract: Background In order to retrieve useful information from scientific literature and electronic medical records (EMR) we developed an ontology specific for Multiple Sclerosis (MS). Methods The MS Ontology was created using scientific literature and expert review under the Protégé OWL environment. We developed a dictionary with semantic synonyms and translations to different languages for mining EMR. The MS Ontology was integrated with other ontologies and dictionaries (diseases/comorbidities, gene/protein, pathways, drug) into the text-mining tool SCAIView. We analyzed the EMRs from 624 patients with MS using the MS ontology dictionary in order to identify drug usage and comorbidities in MS. Testing competency questions and functional evaluation using F statistics further validated the usefulness of MS ontology. Results Validation of the lexicalized ontology by means of named entity recognition-based methods showed an adequate performance (F score = 0.73). The MS Ontology retrieved 80% of the genes associated with MS from scientific abstracts and identified additional pathways targeted by approved disease-modifying drugs (e.g. apoptosis pathways associated with mitoxantrone, rituximab and fingolimod). The analysis of the EMR from patients with MS identified current usage of disease modifying drugs and symptomatic therapy as well as comorbidities, which are in agreement with recent reports. Conclusion The MS Ontology provides a semantic framework that is able to automatically extract information from both scientific literature and EMR from patients with MS, revealing new pathogenesis insights as well as new clinical information.
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It is part of: PLoS One, 2015, vol. 10, num. 2
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ISSN: 1932-6203
Appears in Collections:Articles publicats en revistes (Medicina)

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