Roque FS et al, PLoS Comput Biol, 7(8)
Text mining and information extraction can be seen as the challenge of converting information hidden in text into manageable data. We have used text mining to automatically extract clinically relevant terms from 5543 psychiatric patient records and map these to disease codes in the International Classification of Disease ontology (ICD10). Mined codes were supplemented by existing coded data. For each patient we constructed a phenotypic profile of associated ICD10 codes. This allowed us to cluster patients together based on the similarity of their profiles. The result is a patient stratification based on more complete profiles than the primary diagnosis, which is typically used.
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26 August 2011 | No Comments »
Categories: Science | Country: Denmark | EHR: EHR, EHR Denmark | Tag(s): ICD-10, Text Mining
Collier, Nigel, Journal of Biomedical Semantics, 1(1)
Background
Accurate and timely detection of public health events of international concern is necessary to help support risk assessment and response and save lives. Novel event-based methods that use the World Wide Web as a signal source offer potential to extend health surveillance into areas where traditional indicator networks are lacking. In this paper we address the issue of systematically evaluating online health news to support automatic alerting using daily disease-country counts text mined from real world data using BioCaster. For 18 data sets produced by BioCaster, we compare 5 aberration detection algorithms (EARS C2, C3, W2, F-statistic and EWMA) for performance against expert moderated ProMED-mail postings.
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4 April 2010 | No Comments »
Categories: Science | Tag(s): Disease Surveillance, Online, Public Health, Text Mining
Healthcare IT
“While using usual data mining techniques should have been fine, clinical data is frequently entered as free-text. The great complexity and user-unfriendliness of interfaces that force clinical care providers to enter data in structured form with adequate degree of granularity only is a great disincentive.
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8 December 2009 | No Comments »
Categories: News | Country: United States | EHR: EHR, EHR USA | Tag(s): Data Mining, Terminology, Text Mining
