Publication
Extracting Adverse Drug Effects from User Experiences: A Baseline
| dc.contributor.author | Abrantes, Diogo | |
| dc.contributor.author | Cordeiro, João | |
| dc.date.accessioned | 2020-02-07T14:03:13Z | |
| dc.date.available | 2020-02-07T14:03:13Z | |
| dc.date.issued | 2018-06-18 | |
| dc.description.abstract | It has been proved that pharmacovigilance benefits from the analysis and extraction of user-generated data from blogs, medical forums or other social networks, regarding adverse effect mentions or complaints that occur from taking certain drugs. Data mining, machine learning, pattern recognition, content summarization, and natural language processing techniques are often used in this field with promising results. However, there are still several difficulties concerning the extraction, as the highly domain-specific vocabulary presents a few challenges. This is mainly because patients like to use idiomatic or vernacular expressions along with descriptive symptom explanations, which tend to deviate from grammatical rules or expected terms. To address this issue, we propose a well-curated baseline. We believe that building a specific lexicon, identifying common linguistic patterns and observing certain phrasal structures is key to first understanding how a user generates contents online. From there, we can later develop sets of tailored rules that will allow data classification/extraction systems to potentially improve their efficiency at these tasks. | pt_PT |
| dc.description.sponsorship | This work was supported by Project NORTE-01- 0145-FEDER-000016 (NanoSTIMA), which is financed by the North Portugal Regional Operational Programme (NORTE2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF) | |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | D. Abrantes and J. Cordeiro, "Extracting Adverse Drug Effects from User Experiences: A Baseline," 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS), Karlstad, 2018, pp. 405-410. | pt_PT |
| dc.identifier.doi | 10.1109/CBMS.2018.00077 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.6/9114 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Institute of Electrical and Electronics Engineers | pt_PT |
| dc.relation.publisherversion | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8417272&isnumber=8417175 | pt_PT |
| dc.subject | Pharmacovigilance | pt_PT |
| dc.subject | Adverse effects | pt_PT |
| dc.subject | Information extraction | pt_PT |
| dc.subject | Natural language processing | pt_PT |
| dc.title | Extracting Adverse Drug Effects from User Experiences: A Baseline | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Karlstad, Sweden | pt_PT |
| oaire.citation.endPage | 410 | pt_PT |
| oaire.citation.startPage | 405 | pt_PT |
| oaire.citation.title | 31st International Symposium on Computer-Based Medical Systems (CBMS) | pt_PT |
| person.familyName | Abrantes | |
| person.familyName | Cordeiro | |
| person.givenName | Diogo | |
| person.givenName | João Paulo da Costa | |
| person.identifier.ciencia-id | 7112-204F-E5DC | |
| person.identifier.orcid | 0000-0003-3038-1732 | |
| person.identifier.orcid | 0000-0003-0466-1618 | |
| rcaap.embargofct | Copyright cedido à editora no momento da publicação | pt_PT |
| rcaap.rights | closedAccess | pt_PT |
| rcaap.type | article | pt_PT |
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