Design and Evaluation of the iMed Intelligent Medical Search Engine

Searching for medical information on the Web is popular and important. However, medical search has its own unique requirements that are poorly handled by existing medical Web search engines. This paper presents iMed, the first intelligent medical Web search engine that extensively uses medical knowledge and questionnaire to facilitate ordinary Internet users to search for medical information. iMed introduces and extends expert system technology into the search engine domain. It uses several key techniques to improve its usability and search result quality. First, since ordinary users often cannot clearly describe their situations due to lack of medical background, iMed uses a questionnaire-based query interface to guide searchers to provide the most important information about their situations. Second, iMed uses medical knowledge to automatically form multiple queries from a searcher' answers to the questions. Using these queries to perform search can significantly improve the quality of search results. Third, iMed structures all the search results into a multi-level hierarchy with explicitly marked medical meanings to facilitate searchers' viewing. Lastly, iMed suggests diversified, related medical phrases at each level of the search result hierarchy. These medical phrases are extracted from the MeSH ontology and can help searchers quickly digest search results and refine their inputs. We evaluated iMed under a wide range of medical scenarios. The results show that iMed is effective and efficient for medical search.