Text categorization models for retrieval of high quality articles in internal medicine
Aphinyanaphongs, Y; Aliferis, C F
The discipline of Evidence Based Medicine (EBM) studies formal and quasi-formal methods for identifying high quality medical information and abstracting it in useful forms so that patients receive the best customized care possible [1]. Current computer-based methods for finding high quality information in PubMed and similar bibliographic resources utilize search tools that employ preconstructed Boolean queries. These clinical queries are derived from a combined application of (a) user interviews, (b) ad-hoc manual document quality review, and (c) search over a constrained space of disjunctive Boolean queries. The present research explores the use of powerful text categorization (machine learning) methods to identify content-specific and high-quality PubMed articles. Our results show that models built with the proposed approach outperform the Boolean based PubMed clinical query filters in discriminatory power
PMCID:1480096
PMID: 14728128
ISSN: 1559-4076
CID: 87002
Computational resolving power improvement for the scanning laser ophthalmoscope [Meeting Abstract]
O'Connor, N; Aphinyanaphongs, Y; Zinser, G; Bartsch, D; Freeman, W; Flanagan, J; Hutchins, N; Hudson, C; Holmes, T
ISI:000079269200664
ISSN: 0146-0404
CID: 106430