Paper Info
Title
Medication information extraction with linguistic pattern matching and semantic rules.
Abstract
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.
Year
DOI
Venue
2010
10.1136/jamia.2010.003657
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
Keywords
Field
DocType
medical records,gold standard,information extraction,web pages,rule based,natural language processing,pattern matching
Data mining,Web page,Computer science,Artificial intelligence,Natural language processing,Syntax,Heuristic,Information retrieval,Ranking,Information extraction,Unified Medical Language System,Pattern matching,Semantics
Journal
Volume
Issue
ISSN
17
5
1067-5027
Citations 
PageRank 
References 
28
1.88
7
Authors
4
Name
Order
Citations
PageRank
Irena Spasić135432.55
Farzaneh Sarafraz2664.37
John A. Keane369592.81
Goran Nenadic422813.18