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- W2101386052 abstract "We investigate the task of assigning medical events in clinical narratives to discrete time-bins. The time-bins are defined to capture when a medical event occurs relative to the hospital admission date in each clinical narrative. We model the problem as a sequence tagging task using Conditional Random Fields. We extract a combination of lexical, section-based and temporal features from medical events in each clinical narrative. The sequence tagging system outperforms a system that does not utilize any sequence information modeled using a Maximum Entropy classifier. We present results with both hand-tagged as well as automatically extracted features. We observe over 8% improvement in overall tagging accuracy with the inclusion of sequence information." @default.
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- W2101386052 date "2012-06-08" @default.
- W2101386052 modified "2023-09-26" @default.
- W2101386052 title "Temporal Classification of Medical Events" @default.
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