Meide S Anção | PubMed Health

PubMed2004

An implementation of the trigram phrase matching method for text similarity problems.

The representation of texts by term vectors with element values calculated by a TFIDF method yields to significant results in text similarity problems, such as finding related documents in bibliographic or full-text databases and identifying MeSH concepts from medical texts by lexical approach and also harmonizing journal citation in ISI/SciELO references and normalizing author's affiliation in MEDLINE. Our work considered "trigrams" as the terms (elements) of a term vector representing a text, according to the Trigram Phrase Matching published by the NLM's Indexing Initiative and its logarithmic Term Frequency-Inverse Document Frequency method for term weighting. Trigrams are overlapping 3-char strings from a text, extracted by a couple of rules, and a trigram matching method may improve the probability of identifying synonym phrases or similar texts. The matching process was implemented as a simple algorithm, and requires a certain amount of computer resources. An efficiency-focused C-programming was adopted. In addition, some heuristic rules improved the efficiency of the method and made it feasible a regular "find your scientific production in SciELO collection" information service. We describe an implementation of the Trigram Matching method, the software tool we developed and a set of experimental parameters for the above results.

Abstracting and Indexing↗

PubMed2003

[Computing in medical practice].

OBJECTIVES: Currently, information technology is part of several aspects of our daily life. The objective of this paper is to analyze and discuss the use of information technology in both medical education and/or medical practice. SOURCES: Information was gathered through non-systematic bibliographic review, including articles, official regulations, book chapters and annals. Direct search and search of electronic databanks in Medline and Lilacs databases were also performed. SUMMARY OF THE FINDINGS: This paper was structured in topics. First, there is a discussion on the electronic medical record. The following aspects are presented: history, functions, costs, benefits, ethical and legal issues, and positive and negative characteristics. Medical decision-support systems are also evaluated in view of the huge amount of information produced every year regarding healthcare. The impact of the Internet on the production and diffusion of knowledge is also analyzed. Telemedicine is assessed, since it presents new challenges to medical practice, and raises important ethical issues such as "virtual medical consultation." Finally, a practical experience of modernization of a pediatric outpatient center by the introduction of computers and telecommunication tools is described. CONCLUSIONS: Medical computing offers tools and instruments that support the administrative organization of medical visits, gather, store and process patient's data, generate diagnoses, provide therapeutical advice and access to information in order to improve medical knowledge and to make it available whenever and wherever adequate decision-making is required.

Decision Support Systems, Clinical↗