Abstract
Despite advances in concept extraction from free text, finding meaningful health related information from online patient forums still poses a significant challenge. Here we demonstrate how structured information can be extracted from posts found in such online health related forums by forming relationships between a drug/treatment and a symptom or side effect, including the polarity/sentiment of the patient. In particular, a rule-based natural language processing (NLP) system is deployed, where information in sentences is linked together though anaphora resolution. Our NLP relationship extraction system provides a strong baseline, achieving an F1 score of over 80% in discovering the said relationships that are present in the posts we analysed.
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Hasan, A., Levene, M., & Weston, D. J. (2017). Natural Language Analysis of Online Health Forums. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10584 LNCS, pp. 125–137). Springer Verlag. https://doi.org/10.1007/978-3-319-68765-0_11
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