  Personal health mention detection deals with predicting whether or not a
given sentence is a report of a health condition. Past work mentions errors in
this prediction when symptom words, i.e. names of symptoms of interest, are
used in a figurative sense. Therefore, we combine a state-of-the-art figurative
usage detection with CNN-based personal health mention detection. To do so, we
present two methods: a pipeline-based approach and a feature augmentation-based
approach. The introduction of figurative usage detection results in an average
improvement of 2.21% F-score of personal health mention detection, in the case
of the feature augmentation-based approach. This paper demonstrates the promise
of using figurative usage detection to improve personal health mention
detection.
