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dc.contributor.author de Araujo, Adriana Peter Rodrigues -
dc.contributor.author de Araujo, Maria Carolina Macedo -
dc.contributor.author Cavalcanti, Thiago Coutinho -
dc.contributor.author de Lacerda Vidal, Claudia Fernanda -
dc.contributor.author da Silva, Marilu Gomes Netto Monte -
dc.date.accessioned 2020-09-22T08:30:20Z -
dc.date.available 2020-09-22T08:30:20Z -
dc.date.created 2020-09-16 -
dc.date.issued 2020-11 -
dc.identifier.issn 0140-0118 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/12399 -
dc.description.abstract Dengue, Zika, and chikungunya are epidemic diseases transmitted by the Aedes mosquito. These virus infections can be so severe to the point of bringing on mobility and neurological problems, or even death. Expert systems (ES) can be used as tools for the identification of patterns intended to solve problems in the same way as a professional specialist would. This work aimed to develop an ES in the form of an Android application to serve as a supportive tool in the diagnosis of these arboviruses. The goal is to associate the set of symptoms from a patient to a score related to the likelihood of them having these diseases. To make this possible, we implemented a rule-based ES which considers the presence of symptoms itself and the relation between them to associate the case under analysis to others found in the literature. We performed 96 tests (32 for each illness), and our system had a success rate of 96.88%. Resident physicians of a public hospital also analyzed these clinical cases and achieved an average success rate of 72.92%. Comparing the results of the method proposed and errors made by health professionals, we showed an improvement in the effectiveness of clinical diagnoses. [Figure not available: see fulltext.]. © 2020, International Federation for Medical and Biological Engineering. -
dc.language English -
dc.publisher Springer -
dc.title DZC DIAG: mobile application based on expert system to aid in the diagnosis of dengue, Zika, and chikungunya -
dc.type Article -
dc.identifier.doi 10.1007/s11517-020-02233-6 -
dc.identifier.scopusid 2-s2.0-85089861451 -
dc.identifier.bibliographicCitation Medical and Biological Engineering and Computing, v.58, no.11, pp.2657 - 2672 -
dc.description.isOpenAccess FALSE -
dc.subject.keywordAuthor Chikungunya virus -
dc.subject.keywordAuthor Dengue -
dc.subject.keywordAuthor Expert system -
dc.subject.keywordAuthor mHealth -
dc.subject.keywordAuthor Zika virus -
dc.subject.keywordPlus VIRUS -
dc.subject.keywordPlus TRANSMISSION -
dc.subject.keywordPlus COINFECTION -
dc.subject.keywordPlus VECTOR -
dc.citation.endPage 2672 -
dc.citation.number 11 -
dc.citation.startPage 2657 -
dc.citation.title Medical and Biological Engineering and Computing -
dc.citation.volume 58 -
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