Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/9735
Título: | Knowledge discovery methodology for medical reports |
Autor(es): | Alves, Victor Pinheiro, Vitor |
Palavras-chave: | SOI SOA Open-ESB BPEL Data Mining YALE DICOM HL7 |
Data: | 2009 |
Citação: | PORTUGUESE CONFERENCE ON ARTIFICIAL INTELLIGENCE, 14, Aveiro, Portugal, 2009 – “EPIA2009”. [Aveiro : Universidade de Aveiro, 2009]. ISBN 978-972-96895-4-3. |
Resumo(s): | Medical reports contain valuable information, not only for the patient that waits for the results but also the latent knowledge that is possible to extract from them. The recent introduction of standard structured formats like the Digital Imaging and Communications in Medicine Structured Report and the Clinical Document Architecture Health Level Seven provide an efficient generation, distribution, and management mechanism. Also, they provide an intuitive and effective manner of information representation, unlike the traditional plain text format. In this paper we present a knowledge discovery methodology for structured report interchange based on plain text medical reports using YALE, a leading open-source data mining tool and Open-ESB platform that provides conversion, parsing, different protocols and message formats interchange capabilities. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/9735 |
ISBN: | 978-972-96895-4-3 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | DI/CCTC - Artigos (papers) |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
EPIA2009_117.pdf | 193,86 kB | Adobe PDF | Ver/Abrir |