Automatic Knowledge Extraction Supported by Semantic Enrichment in Medical Records

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.creatorValencio, Carlos Roberto [UNESP]-
Autor(es): dc.creatorMartins, Rodrigo Dulizio [UNESP]-
Autor(es): dc.creatorMarioto, Matheus Henrique [UNESP]-
Autor(es): dc.creatorPizzigatti Correa, Pedro Luiz-
Autor(es): dc.creatorBabini, Maurizio [UNESP]-
Autor(es): dc.creatorHorng, S. J.-
Data de aceite: dc.date.accessioned2022-02-22T00:12:41Z-
Data de disponibilização: dc.date.available2022-02-22T00:12:41Z-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2020-12-09-
Data de envio: dc.date.issued2013-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/PDCAT.2013.19-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/197450-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/197450-
Descrição: dc.descriptionThe volume of digital information is growing considerably in the last two decades and there is currently a huge concern about obtaining this content quickly and effectively. In the health sector it is not different; to retrieve medical records that obtain relevant information about treatments and progresses of clinical conditions may speed up new patients' diagnosis. In this work it is described a framework proposed for automatically indexing information based on semantics and on text mining techniques. This task should work in parallel with the insertion of data into electronic records. The original contributions come down to search engine in texts organized so as to potentiate the amount of results obtained, as evidenced by the experiments carried out. The stored information is automatically fragmented into words, which have a semantic dictionary based on a framework that enables the information retrieval through semantics.-
Descrição: dc.descriptionSao Paulo State Univ, Dept Ciencias Comp & Estat, Sao Paulo, Brazil-
Descrição: dc.descriptionUniv Sao Paulo, Dept Engn Comp & Sistemas Digitais, Sao Paulo, Brazil-
Descrição: dc.descriptionSao Paulo State Univ, Dept Letras Modernas, Sao Paulo, Brazil-
Descrição: dc.descriptionSao Paulo State Univ, Dept Ciencias Comp & Estat, Sao Paulo, Brazil-
Descrição: dc.descriptionSao Paulo State Univ, Dept Letras Modernas, Sao Paulo, Brazil-
Formato: dc.format79-83-
Idioma: dc.languageen-
Publicador: dc.publisherIeee-
Relação: dc.relation2013 International Conference On Parallel And Distributed Computing, Applications And Technologies (pdcat)-
???dc.source???: dc.sourceWeb of Science-
Palavras-chave: dc.subjectsemantics-
Palavras-chave: dc.subjecttext mining-
Palavras-chave: dc.subjectknowledge extraction-
Palavras-chave: dc.subjectTFxIDF(Term Frequency x Inverse Document)-
Título: dc.titleAutomatic Knowledge Extraction Supported by Semantic Enrichment in Medical Records-
Aparece nas coleções:Repositório Institucional - Unesp

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