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Bibliographic search engines allow endless possibilities for building queries based on specific words or phrases in article titles and abstracts, indexing terms, and other attributes. Unfortunately, deciding which attributes to use in a methodologically sound query is a non-trivial process. In this paper, we describe a system to help with this task, given an example set of PubMed articles to retrieve and a corresponding set of articles to exclude. The system provides the users with unigram and bigram features from the title, abstract, MeSH terms, and MeSH qualifier terms in decreasing order of precision, given a recall threshold. From this information and their knowledge of the domain, users can formulate a query and evaluate its performance. We apply the system to the task of distinguishing original research articles of functional magnetic resonance imaging (fMRI) of sensorimotor function from fMRI studies of higher cognitive functions.

Formulating MEDLINE queries for article retrieval based on PubMed exemplars