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

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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.

Graphical abstract

Figure - DZC DIAG Operating Flowchart: the physicians record patients’ data and answer a series of questions related to the patient’s symptoms; after all the questions, the result is generated by the expert system (score for dengue, Zika, and chikungunya); and it is saved in the same device where the test was done and uploaded online to a FTP.

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Acknowledgments

The authors would like to thank the Federal University of Pernambuco for the structure required for the development of the project and the physicians of the Clinical Hospital for their contribution to the tests.

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Authors and Affiliations

  1. Biomedical Engineering Department, University of Southern California, Los Angeles, USA

    Adriana Peter Rodrigues de Araújo

  2. Biomedical Engineering Department, Federal University of Pernambuco, Av. da Arquitetura, s/n – Cidade Universitária, Recife, PE, CEP: 50740-550, Brazil

    Maria Carolina Macedo de Araujo & Marilú Gomes Netto Monte da Silva

  3. Information and Communication Engineering Department, Daegu Gyeongbuk Institute of Science and Technology, Daegu, South Korea

    Thiago Coutinho Cavalcanti

  4. Tropical Medicine Department, Federal University of Pernambuco, Recife, Brazil

    Cláudia Fernanda de Lacerda Vidal

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  1. Adriana Peter Rodrigues de Araújo
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  2. Maria Carolina Macedo de Araujo
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  3. Thiago Coutinho Cavalcanti
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  4. Cláudia Fernanda de Lacerda Vidal
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  5. Marilú Gomes Netto Monte da Silva
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Correspondence to Marilú Gomes Netto Monte da Silva.

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de Araújo, A.P.R., de Araujo, M.C.M., Cavalcanti, T.C. et al. DZC DIAG: mobile application based on expert system to aid in the diagnosis of dengue, Zika, and chikungunya. Med Biol Eng Comput 58, 2657–2672 (2020). https://doi.org/10.1007/s11517-020-02233-6

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