| Medication information extraction with linguistic pattern matching and semantic rules. | |
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MedLine Citation:
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PMID: 20819858 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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OBJECTIVE: This study presents a system developed for the 2009 i2b2 Challenge in Natural Language Processing for Clinical Data, whose aim was to automatically extract certain information about medications used by a patient from his/her medical report. The aim was to extract the following information for each medication: name, dosage, mode/route, frequency, duration and reason. DESIGN: The system implements a rule-based methodology, which exploits typical morphological, lexical, syntactic and semantic features of the targeted information. These features were acquired from the training dataset and public resources such as the UMLS and relevant web pages. Information extracted by pattern matching was combined together using context-sensitive heuristic rules. MEASUREMENTS: The system was applied to a set of 547 previously unseen discharge summaries, and the extracted information was evaluated against a manually prepared gold standard consisting of 251 documents. The overall ranking of the participating teams was obtained using the micro-averaged F-measure as the primary evaluation metric. RESULTS: The implemented method achieved the micro-averaged F-measure of 81% (with 86% precision and 77% recall), which ranked this system third in the challenge. The significance tests revealed the system's performance to be not significantly different from that of the second ranked system. Relative to other systems, this system achieved the best F-measure for the extraction of duration (53%) and reason (46%). CONCLUSION: Based on the F-measure, the performance achieved (81%) was in line with the initial agreement between human annotators (82%), indicating that such a system may greatly facilitate the process of extracting relevant information from medical records by providing a solid basis for a manual review process. |
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Authors:
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Irena Spasic; Farzaneh Sarafraz; John A Keane; Goran Nenadic |
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Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Journal of the American Medical Informatics Association : JAMIA Volume: 17 ISSN: 1527-974X ISO Abbreviation: J Am Med Inform Assoc Publication Date: 2010 Sep-Oct |
Date Detail:
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Created Date: 2010-09-07 Completed Date: 2010-11-15 Revised Date: 2011-09-13 |
Medline Journal Info:
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Nlm Unique ID: 9430800 Medline TA: J Am Med Inform Assoc Country: United States |
Other Details:
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Languages: eng Pagination: 532-5 Citation Subset: IM |
Affiliation:
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Cardiff School of Computer Science & Informatics, Cardiff University, Cardiff, UK. i.spasic@cs.cardiff.ac.uk |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Artificial Intelligence Electronic Health Records* Humans Information Storage and Retrieval / methods* Linguistics Natural Language Processing* Pharmaceutical Preparations* Semantics |
| Grant Support | |
ID/Acronym/Agency:
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U54LM008748/LM/NLM NIH HHS; //Biotechnology and Biological Sciences Research Council |
| Chemical | |
Reg. No./Substance:
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0/Pharmaceutical Preparations |
| Comments/Corrections | |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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