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

Araújo, Adriana Peter Rodrigues de; Araujo, Maria Carolina Macedo de; Cavalcanti, Thiago Coutinho; Vidal, Cláudia Fernanda de Lacerda; Silva, Marilú Gomes Netto Monte da

doi:10.1007/s11517-020-02233-6

Cited by 2 publications

(6 citation statements)

References 51 publications

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“…Likewise, a fuzzy system implemented in MATLAB for analyzing the infection level in viral diseases achieved a precision rate of 86.6 [14], indicating that the system developed in this study performs comparably in the early detection of viral diseases. However, the rule-based expert system for arbovirus diagnosis exhibited a 96.88% precision rate [16], surpassing the success rate of medical professionals by a significant margin. In this context, the accuracy of the system in this study is similar, reaching a level of 95% precision.…”

Section: Analysis Of Mean and Standard Deviationmentioning

confidence: 93%

“…Likewise, de Araújo et al [16] contributed to the development of an expert system in the form of an Android application for the diagnosis of dengue, zika, and chikungunya. This expert system associated symptoms with a probability score of suffering from these diseases, with a success rate of 96.88% in tests with 96 cases, exceeding the success rate of resident physicians.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This feature makes it accessible to a large number of users. In contrast, some studies explore different platforms, including the development of specific applications for smartphones [16], [17]. This variation in technological choices highlights the diversity of strategies adopted in research, where the mobility and accessibility of applications for smartphones and computers play a relevant role in the implementation of innovative solutions in the field of health and technology.…”

Section: The Novelty Of the Study Compared To Previous Researchmentioning

confidence: 99%

“…This specific technique, which focuses on symptom-specific logic and data processing, can contribute to diagnostic accuracy. Meanwhile, some studies opted for the implementation of rule-based expert systems [16] and the application of machine learning models, such as the SVM [18].…”

Section: The Novelty Of the Study Compared To Previous Researchmentioning

confidence: 99%

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Intelligent preliminary diagnosis system for diseases with similar clinical presentation

Andrade-Arenas,

Yactayo-Arias

2024

IJEECS

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Accurately identifying diseases with similar symptoms, especially in resource-limited medical settings, is a key challenge to diagnostic accuracy. This paper presents a preliminary diagnostic system to address the challenge of diagnosing diseases with similar symptoms. The system has been implemented using the PyQt5 library and employs a unique symptom identification algorithm developed in Python. Furthermore, to carry out the diagnosis, it uses comma-separated values (CSV) and excel files as databases where the diseases and their respective symptoms are stored. The results show that the system has a precision of 95%, a sensitivity of 90%, and a specificity of 93% after evaluating 35 clinical cases covering seven diseases with similar initial symptoms, namely: dengue, zika, chikungunya, COVID-19, influenza, monkey-pox, and the common cold. Furthermore, the positive evaluation of the technical performance of the system by experts supports its practical feasibility and its potential as a valuable tool in medical practice. In conclusion, the system diagnoses diseases by analyzing the symptoms of the information file, highlighting its usefulness in improving the diagnostic accuracy of similar cases and optimizing medical care for the benefit of patients.

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Section: Analysis Of Mean and Standard Deviationmentioning

confidence: 93%

Section: Literature Reviewmentioning

confidence: 99%

Section: The Novelty Of the Study Compared To Previous Researchmentioning

confidence: 99%

Section: The Novelty Of the Study Compared To Previous Researchmentioning

confidence: 99%

See 2 more Smart Citations

Intelligent preliminary diagnosis system for diseases with similar clinical presentation

Andrade-Arenas,

Yactayo-Arias

2024

IJEECS

View full text Add to dashboard Cite

show abstract

“…de Araújo et al [18], developed an expert system based on an android mobile app with the aim of assisting in the diagnosis of dengue, zika, and chikungunya infections. Additionally, one of its goals is to compare a patient's symptoms to a score that represents the likelihood that they have the disease at issue.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of a Prototype Mobile Application Based on an Expert System for the Diagnosis of Diseases Transmitted by the Aedes Aegypti Mosquito

Jaúregui-Velarde,

Molina-Velarde,

Yactayo-Arias

et al. 2023

Int. J. Onl. Eng.

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The Aedes aegypti mosquito transmits the dengue, zika, and chikungunya viruses, endangering the health and lives of people in affected countries due to a lack of timely diagnosis. The objective of this study is to design and evaluate the feasibility of a mobile application based on an expert system for early diagnosis of diseases transmitted by the Aedes aegypti mosquito. The Buchanan methodology was used to develop the application. The results obtained show that the proposed mobile application has a diagnostic accuracy of 83%, a sensitivity of 91%, a specificity of 63%, and an error rate of 17%. The technical aspects of the application were also evaluated through a questionnaire administered to five computer experts. The results showed that the technical aspects of the application received an average rating of 3.91 out of a maximum of 5, with a standard deviation of 0.482. In addition, the usability of the application was evaluated using the standardized System Usability Scale (SUS), which was administered to a total of 15 users. The results of this evaluation showed that the application received an average score of 83 on the SUS scale, indicating a positive level of usability. In conclusion, the results support the effectiveness and potential of the application for the early diagnosis of diseases transmitted by the Aedes aegypti mosquito, providing a useful tool for the rapid detection of these diseases. Although it requires more attention to specificity and error rate to improve the accuracy of the diagnosis.

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

Cited by 2 publications

References 51 publications

Intelligent preliminary diagnosis system for diseases with similar clinical presentation

Intelligent preliminary diagnosis system for diseases with similar clinical presentation

Evaluation of a Prototype Mobile Application Based on an Expert System for the Diagnosis of Diseases Transmitted by the Aedes Aegypti Mosquito

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