Cited 0 time in webofscience Cited 0 time in scopus

DZC DIAG: mobile application based on expert system to aid in the diagnosis of dengue, Zika, and chikungunya

Title
DZC DIAG: mobile application based on expert system to aid in the diagnosis of dengue, Zika, and chikungunya
Authors
de Araujo, Adriana Peter Rodriguesde Araujo, Maria Carolina MacedoCavalcanti, Thiago Coutinhode Lacerda Vidal, Claudia Fernandada Silva, Marilu Gomes Netto Monte
DGIST Authors
de Araujo, Adriana Peter Rodrigues; de Araujo, Maria Carolina Macedo; Cavalcanti, Thiago Coutinho; de Lacerda Vidal, Claudia Fernanda; da Silva, Marilu Gomes Netto Monte
Issue Date
2020-11
Citation
Medical and Biological Engineering and Computing, 58(11), 2657-2672
Type
Article
Article Type
Article
Author Keywords
Chikungunya virusDengueExpert systemmHealthZika virus
Keywords
VIRUSTRANSMISSIONCOINFECTIONVECTOR
ISSN
0140-0118
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.
URI
http://hdl.handle.net/20.500.11750/12399
DOI
10.1007/s11517-020-02233-6
Publisher
Springer
Files:
There are no files associated with this item.
Collection:


qrcode mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE