The constantly growing publication rate of medical research articles puts
increasing pressure on medical specialists who need to be aware of the
recent developments in their field. The currently used literature retrieval
systems allow researchers to find specific papers; however the search task
is still repetitive and time-consuming.
In this paper we describe a system that retrieves medical publications by
automatically generating queries based on data from an electronic patient
record. This allows the doctor to focus on medical issues and provide an
improved service to the patient, with higher confidence that it is
underpinned by current research.
Our research prototype automatically generates query terms based on the
patient record and adds weight factors for each term. Currently the
patient’s age is taken into account with a fuzzy logic derived
weight, and terms describing blood-related anomalies are derived from recent
blood test results. Conditionally selected homonyms are used for query
The query retrieves matching records from a local index of PubMed
publications and displays results in descending relevance for the given
patient. Recent publications are clearly highlighted for instant recognition
by the researcher.
Nine medical specialists from the Royal Adelaide Hospital evaluated the
system and submitted pre-trial and post-trial questionnaires. Throughout the
study we received positive feedback as doctors felt the support provided by
the prototype was useful, and which they would like to use in their daily
By supporting the time-consuming task of query formulation and iterative
modification as well as by presenting the search results in order of
relevance for the specific patient, literature retrieval becomes part of the
daily workflow of busy professionals.