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We used the Side Effect Resource database and DailyMed to generate a comparison dataset of 1159 Structured Product Labels. We processed the Adverse Reaction section of these Structured Product Labels with the Event-based Text-mining of Health Electronic Records system and evaluated its ability to extract and encode Adverse Event terms to Medical Dictionary for Regulatory Activities Preferred Terms. A small sample of 100 labels was then selected for further analysis. Of the 100 labels, Event-based Text-mining of Health Electronic Records achieved a precision and recall of 81\u2009percent and 92\u2009percent, respectively. This study demonstrated Event-based Text-mining of Health Electronic Record\u2019s ability to extract and encode Adverse Event terms from Structured Product Labels which may potentially support multiple pharmacoepidemiological tasks.<\/jats:p>","DOI":"10.1177\/1460458217749883","type":"journal-article","created":{"date-parts":[[2018,1,23]],"date-time":"2018-01-23T05:26:41Z","timestamp":1516685201000},"page":"1232-1243","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":14,"title":["Adverse Event extraction from Structured Product Labels using the Event-based Text-mining of Health Electronic Records (ETHER) 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