title: Personalizing retrieval of journal articles for patient care.
abstract: We present a system for patient-specific searches on a database of medical journal articles which uses natural language techniques to match search results against patient records. We performed an information retrieval experiment comparing the performance of this system to two strategies, one of which uses extensive medical knowledge, while the other uses the same patient information our system has. The results show that our system is useful in improving recall over the strategy simulating a human specialist, and clearly outperforms the strategy of using the patient record content without intelligent processing.
authors.affiliation: Department of Computer Science, Columbia University, New York, NY 10027, USA. teufel@cs.columbia.edu
authors.forename: S
authors.initials: S
authors.lastname: Teufel
authors.forename: V
authors.initials: V
authors.lastname: Hatzivassiloglou
authors.forename: S
authors.initials: S
authors.lastname: Teufel
authors.forename: K R
authors.initials: KR
authors.lastname: McKeown
authors.forename: D A
authors.initials: DA
authors.lastname: Jordan
authors.forename: K M
authors.initials: KM
authors.lastname: Dunn
authors.forename: S
authors.initials: S
authors.lastname: Sigelman
authors.forename: A
authors.initials: A
authors.lastname: Kushniruk
mesh_terms: D000465:Algorithms; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D016239:MEDLINE; D009323:Natural Language Processing; D005791:Patient Care; D013358:Subject Headings