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CISTI'2017 - 12ª Conferência Ibérica de Sistemas e Tecnologias de Informação

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Computational Semiotics Applied Medical to Semiology

Health Sciences literature reveals that medical errors are the third cause of death in the United States [1]. In Brazil, researchers from the Federal University of Minas Gerais, conducted a study which estimated that in 2015 the health system failures in Brazil caused roughly about 434,000 deaths. In this alarming scenario, the main causes of death are the lack of physical structure, lack of update protocol in the quality of new pathology information, and errors in diagnosis and treatment. The lack of standardization of medical terms and popular nomenclatures that refer to the same condition problems such as ambiguity, vagueness description of symptoms(e.g. difference between medical and colloquial terms), difficulty in treating personal information, may also generate further problems due to the hard classification, which directly implies the appropriate functioning of a computer support decision system. Additionally, the information sources and different formats in which medical information are found generate extra challenges for interoperability. This paper describes the idea and preliminary results to address this semantic problem, by means of Artificial Intelligence techniques and adaptive Semiotic Machine.

Author(s):

Rui Pontes Filho    
Universidade de Pernambuco
Brazil

Fernando Lima Neto    
Universidade de Pernambuco
Brazil

Denis Martins    
Universidade de Pernambuco
Brazil

Geraldo Barros    
Universidade de Pernambuco
Brazil

 

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