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- W2106580701 abstract "Human annotators and natural language applications are able to identify smoking status from discharge summaries with high accuracy when explicit evidence regarding their smoking status is present in the summary. We explore the possibility of identifying the smoking status from discharge summaries when these smoking terms have been removed. We present results using a Na¨ove Bayes classifier on a smoke-blind set of discharge summaries and compare this to the performance of human annotators on the same dataset." @default.
- W2106580701 created "2016-06-24" @default.
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- W2106580701 date "2006-01-01" @default.
- W2106580701 modified "2023-09-27" @default.
- W2106580701 title "Identifying Smoking Status From Implicit Information in Medical Discharge Summaries" @default.
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