Building a knowledge base to support a digital library.
As part of an effort to develop a knowledge base to support searching online medical literature according to individual needs, we have studied the possibility of using the co-occurrence of MeSH terms in MEDLINE citations associated with the search strategies optimal for evidence based medicine to automated construction of a knowledge base. This study evaluates the relevance of the relationships between the semantic relationship pairs generated by the process, and the clinical validity of the semantic types involved in the process. From the semantic pairs proposed by our method, a group of clinicians judge sixty percent to be relevant. The remaining forty percent included semantic types considered unimportant by clinicians. The knowledge extraction method showed reasonable results. We believe it can be appropriate for the task of retrieving information from the medical record in order to guide users during a searching and retrieval process. Future directions include the validation of the knowledge, based on an evaluation of system performance.
Mendonça
E A
EA
Department of Medical Informatics, Columbia University, New York, NY 10032, USA. mendonca@dmi.columbia.edu
Cimino
J J
JJ
D000465:Algorithms; D001185:Artificial Intelligence; D002318:Cardiovascular Diseases / Q000628:therapy; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D016239:MEDLINE; D016347:Medical Records Systems, Computerized / Q000458:organization & administration; D009862:Online Systems; D012660:Semantics; D013358:Subject Headings; D011795:Surveys and Questionnaires; D013813:Therapy, Computer-Assisted