Paper Info
Title
On iterative intelligent medical search
Abstract
Searching for medical information on the Web has become highly popular, but it remains a challenging task because searchers are often uncertain about their exact medical situations and unfamiliar with medical terminology. To address this challenge, we have built an intelligent medical Web search engine called iMed, which uses medical knowledge and an interactive questionnaire to help searchers form queries. This paper focuses on iMed's iterative search advisor, which integrates medical and linguistic knowledge to help searchers improve search results iteratively. Such an iterative process is common for general Web search, and especially crucial for medical Web search, because searchers often miss desired search results due to their limited medical knowledge and the task's inherent difficulty. iMed's iterative search advisor helps the searcher in several ways. First, relevant symptoms and signs are automatically suggested based on the searcher's description of his situation. Second, instead of taking for granted the searcher's answers to the questions, iMed ranks and recommends alternative answers according to their likelihoods of being the correct answers. Third, related MeSH medical phrases are suggested to help the searcher refine his situation description. We demonstrate the effectiveness of iMed's iterative search advisor by evaluating it using real medical case records and USMLE medical exam questions.
Year
DOI
Venue
2008
10.1145/1390334.1390338
SIGIR
Keywords
Field
DocType
intelligent medical web search engine,real medical case record,exact medical situation,medical query,iterative search advisor,usmle medical exam question,iterative search process,medical web search,language model,limited medical knowledge,iterative intelligent medical search,intelligent medical web search,medical terminology,medical information,medical knowledge,web search engine
Web search engine,Data mining,Web search query,World Wide Web,Semantic search,Medical terminology,Information retrieval,Iterative and incremental development,Computer science,Medical knowledge,Search analytics,Language model
Conference
Citations 
PageRank 
References 
16
0.98
3
Authors
2
Name
Order
Citations
PageRank
Gang Luo174144.73
Chunqiang Tang2128775.09