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- W2202984025 abstract "AbstractDetermining the efficacy of semantic based searching in the analysis of the epidemiology of Kawasaki Disease as a case study, the MetaMap tool processed 159 MEDLINE abstracts into Unified Medical Language System Semantic Types. Based on a random selection of 79 citations, we identified semantic patterns representing risk factors and incidence data. These patterns were tested on the remainder. Results, compared to a gold standard, were 0.19 sensitivity, 0.47 positive predictive value, and 0.99 specificity for incidence data; and 0.55 sensitivity, 0.55 positive predictive value, and 0.86 specificity for risk factors. Thus, a simple algorithm using semantics produced modest results." @default.
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- W2202984025 date "2002-01-01" @default.
- W2202984025 modified "2023-09-24" @default.
- W2202984025 title "Mining the Epidemiological Literature for Risk Factors and Incidence Data of Kawasaki Disease" @default.
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