Document-level adverse drug reaction event extraction on electronic health records in Spanish
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Redalyc
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| Format: | Artículo científico |
| Langue: | en |
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Sociedad Española para el Procesamiento del Lenguaje Natural
2016
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| _version_ | 1876423933691953152 |
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| author | Sara Santiso |
| author_facet | Sara Santiso |
| contents | Document-level adverse drug reaction event extraction on electronic health records in Spanish Sara Santiso Alicia Pérez Maite Oronoz Koldo Gojenola Arantza Casillas Computación Text Mining Event Extraction Adverse Drug Reactions We outline an Adverse Drug Reaction (ADRs) extraction system for Electronic Health Records (EHRs) written in Spanish. The goal of the system is to assist experts on pharmacy in making the decision of whether a patient suffers from one or more ADRs. The core of the system is a predictive model inferred from a manually tagged corpus that counts on both semantic and syntactically features. This model is able to extract ADRs from disease-drug pairs in a given EHR. Finally, the ADRs automatically extracted are post-processed using a heuristic to present the information in a compact way. This stage reports the drugs and diseases of the document together with their frequency, and it also links the pairs related as ADRs. In brief, the system not only presents the ADRs in the text but also provides concise information on request by experts in pharmacy (the potential users of the system). 2016 artículo científico 1135-5948 https://www.redalyc.org/articulo.oa?id=515754423005 en http://www.redalyc.org/revista.oa?id=5157 Procesamiento del Lenguaje Natural application/pdf Sociedad Española para el Procesamiento del Lenguaje Natural Procesamiento del Lenguaje Natural (España) Num.56 |
| format | Artículo científico |
| id | redalyc_515754423005 |
| institution | Redalyc |
| language | en |
| publishDate | 2016 |
| publisher | Sociedad Española para el Procesamiento del Lenguaje Natural |
| spellingShingle | Document-level adverse drug reaction event extraction on electronic health records in Spanish Sara Santiso Computación Text Mining Event Extraction Adverse Drug Reactions Document-level adverse drug reaction event extraction on electronic health records in Spanish Sara Santiso Alicia Pérez Maite Oronoz Koldo Gojenola Arantza Casillas Computación Text Mining Event Extraction Adverse Drug Reactions We outline an Adverse Drug Reaction (ADRs) extraction system for Electronic Health Records (EHRs) written in Spanish. The goal of the system is to assist experts on pharmacy in making the decision of whether a patient suffers from one or more ADRs. The core of the system is a predictive model inferred from a manually tagged corpus that counts on both semantic and syntactically features. This model is able to extract ADRs from disease-drug pairs in a given EHR. Finally, the ADRs automatically extracted are post-processed using a heuristic to present the information in a compact way. This stage reports the drugs and diseases of the document together with their frequency, and it also links the pairs related as ADRs. In brief, the system not only presents the ADRs in the text but also provides concise information on request by experts in pharmacy (the potential users of the system). 2016 artículo científico 1135-5948 https://www.redalyc.org/articulo.oa?id=515754423005 en http://www.redalyc.org/revista.oa?id=5157 Procesamiento del Lenguaje Natural application/pdf Sociedad Española para el Procesamiento del Lenguaje Natural Procesamiento del Lenguaje Natural (España) Num.56 |
| title | Document-level adverse drug reaction event extraction on electronic health records in Spanish |
| topic | Computación Text Mining Event Extraction Adverse Drug Reactions |
| url | https://www.redalyc.org/articulo.oa?id=515754423005 |