Intelligent medical information filtering.
This paper describes an intelligent information filtering system to assist users to be notified of updates to new and relevant medical information. Among the major problems users face is the large volume of medical information that is generated each day, and the need to filter and retrieve relevant information. The Internet has dramatically increased the amount of electronically accessible medical information and reduced the cost and time needed to publish. The opportunity of the Internet for the medical profession and consumers is to have more information to make decisions and this could potentially lead to better medical decisions and outcomes. However, without the assistance from professional medical librarians, retrieving new and relevant information from databases and the Internet remains a challenge. Many physicians do not have access to the services of a medical librarian. Most physicians indicate on surveys that they do not prefer to retrieve the literature themselves, or visit libraries because of the lack of recent materials, poor organisation and indexing of materials, lack of appropriate and available material, and lack of time. The information filtering system described in this paper records the online web browsing behaviour of each user and creates a user profile of the index terms found on the web pages visited by the user. A relevance-ranking algorithm then matches the user profiles to the index terms of new health care web pages that are added each day. The system creates customised summaries of new information for each user. A user can then connect to the web site to read the new information. Relevance feedback buttons on each page ask the user to rate the usefulness of the page to their immediate information needs. Errors in relevance ranking are reduced in this system by having both the user profile and medical information represented in the same representation language using a controlled vocabulary. This system also updates the user profiles, automatically relieving this burden from the user, but also allowing the user to explicitly state preferences. An initial evaluation of this system was done with health consumers using a web site on consumer health. It was found that users often modified their criteria for what they considered relevant not only between browsing sessions but also during a session. A user's criteria for what is relevant is constantly changing as they interact with the information. New revised metrics of recall and precision are needed to account for the partially relevant judgements and the dynamically changing criteria of users. Future research, development, and evaluation of interactive information retrieval systems will need to take into account the users' dynamically changing criteria of relevance.
Quintana
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New Media Lab, Faculty of Information and Media Studies, the University of Western Ontario, London, Canada. yquint@julian.uwo.ca
D001185:Artificial Intelligence; D016247:Information Storage and Retrieval; D008490:Medical Informatics