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Text Mining Electronic Health Records to Identify Hospital Adverse Events
Lars Ulrik Gerdes, Christian Hardahl
1145
10.3233/978-1-61499-289-9-1145
Studies in Health Technology and Informatics
Volume 192: MEDINFO 2013
Abstract

Manual reviews of health records to identify possible adverse events are time consuming. We are developing a method based on natural language processing to quickly search electronic health records for common triggers and adverse events. Our results agree fairly well with those obtained using manual reviews, and we therefore believe that it is possible to develop automatic tools for monitoring aspects of patient safety.

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