Dynamic generation of a Health Topics Overview from consumer health information documents

Abstract

Online health information use is increasing, but can be too difficult for consumers. We created a system that dynamically generates a health topics overview for consumer health web pages that organises the information into four consumer-preferred categories while displaying topic prevalence through visualisation. It accesses both a consumer health vocabulary and the Unified Medical Language System (UMLS). We evaluated its ability by calculating precision, recall, and F-score for phrase extraction and categorisation. We tested pages from three different consumer web sites. Overall, precision is 82&37;, recall is 75&37;, and F-score is 78&37;, and precision between sites did not significantly differ.

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