Personalized Search of the Medical Literature: An Evaluation

Hatzivassiloglou, Vasileios; Teuel, Simone; Sigelman, Sergey

We describe a system for personalizing a set of medical journal articles (possibly created as the output of a search engine) by selecting those documents that specifically match a patient under care. Key element in our approach is the use of targeted parts of the electronic patient record to serve as a readily available user model for the personalization task. We discuss several enhancements to a TF*IDF based approach for measuring the similarity between articles and the patient record. We also present the results of an experiment involving almost 3,000 relevance judgments by medical doctors. Our evaluation establishes that the automated system surpasses in performance alternative methods for personalizing the set of articles, including keyword-based queries manually constructed by medical experts for this purpose.



More About This Work

Academic Units
Computer Science
Department of Computer Science, Columbia University
Columbia University Computer Science Technical Reports, CUCS-003-03
Published Here
April 26, 2011