Unwanted drug-drug interactions endanger millions of patients each year and burden families and the hospital system with escalating costs. Computer-based alerting systems are designed to prevent these interactions, yet the knowledge bases that support these systems often contain incomplete, clinically insignificant, and inaccurate drug information that can contribute to false alerts and wasted time. It may be possible to improve the content of these drug interaction databases by facilitating access to new or underused sources of drug-drug interaction information. The National Library of Medicine's MEDLINE database represents a respected source of peer-reviewed biomedical citations that would serve as a valuable source of information if the relevant articles could be pinpointed effectively and efficiently. This research compared the classification capabilities of human-generated and computer-generated Boolean queries as methods for locating articles about drug interactions. Two manual queries were assembled by medical librarians specializing in MEDLINE searches, and three computer-based queries were developed using a decision tree modeled on Support Vector Machine output. All five queries were tested on a corpus of manually-labeled positive and negative drug-drug interaction citations. Overall, the study showed that computer-generated queries derived from automated classification techniques have the potential to perform at least as well as manual queries in identifying drug-drug interaction articles in MEDLINE.
| Identifer | oai:union.ndltd.org:VANDERBILT/oai:VANDERBILTETD:etd-11302005-134810 |
| Date | 13 December 2005 |
| Creators | Duda, Stephany Norah |
| Contributors | Randolph A. Miller, Constantin F. Aliferis, Kevin B. Johnson |
| Publisher | VANDERBILT |
| Source Sets | Vanderbilt University Theses |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.vanderbilt.edu/available/etd-11302005-134810/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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