Information Extraction from Medical Social Media

Extracting information from unstructured texts is important since automatic processing and analysis of texts requires structured information. Algorithms and tools are already available for mapping clinical and biomedical documents to concepts of medical terminologies and ontologies. Once applied to a document they provide extracted concepts that represent the content of a document. However, the question is whether these tools are applicable to medical social media. As we have seen in the previous sections, language in medical social media texts differs from language in clinical documents. In this chapter, we will assess the extraction quality of such tools through a qualitative study. The mapping quality of two mapping or named entity recognition tools originally designed for processing clinical texts is compared when they are applied to medical social media text.

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