Diagnosis of SARS-CoV-2 Based on Patient Symptoms and Fuzzy Classifiers

Fray L. Becerra-Suarez; Heber I. Mejia-Cabrera; Víctor A. Tuesta-Monteza; Manuel G. Forero

doi:10.1007/978-3-030-76228-5_35

Diagnosis of SARS-CoV-2 Based on Patient Symptoms and Fuzzy Classifiers

Fray L. Becerra-Suarez, Heber I. Mejia-Cabrera, Víctor A. Tuesta-Monteza, Manuel G. Forero

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The contention, mitigation and prevention measures that governments have implemented around the world do not appear to be sufficient to prevent the spread of SARS-CoV-2. The number of infected and dead continues to rise every day, putting a strain on the capacity and infrastructure of hospitals and medical centers. Therefore, it is necessary to develop new diagnostic methods based on patients' symptoms that allow the generation of early warnings for appropriate treatment. This paper presents a new method in development for the diagnosis of SARS-CoV-2, based on patient symptoms and the use of fuzzy classifiers. Eleven (11) variables were fuzzified. Then, knowledge rules were established and finally, the center of mass method was used to generate the diagnostic results. The method was tested with a database of clinical records of symptomatic and asymptomatic SARS-CoV-2 patients. By testing the proposed model with data from symptomatic patients, we obtained 100% sensitivity and 100% specificity. Patients according to their symptoms are classified into two classes, allowing for the detection of patients requiring immediate attention from those with milder symptoms.

Original language	English
Title of host publication	Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings
Editors	Juan Antonio Lossio-Ventura, Jorge Carlos Valverde-Rebaza, Eduardo Díaz, Hugo Alatrista-Salas
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	484-494
Number of pages	11
ISBN (Print)	9783030762278
DOIs	https://doi.org/10.1007/978-3-030-76228-5_35
State	Published - 2021
Externally published	Yes
Event	7th Annual International Conference on Information Management and Big Data, SIMBig 2020 - Virtual, Online Duration: 1 Oct 2020 → 3 Oct 2020

Publication series

Name	Communications in Computer and Information Science
Volume	1410 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	7th Annual International Conference on Information Management and Big Data, SIMBig 2020
City	Virtual, Online
Period	1/10/20 → 3/10/20

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Keywords

Coronavirus
Covid-19
Diagnosis
Fuzzy classifier
SARS-CoV-2

Access to Document

10.1007/978-3-030-76228-5_35

Cite this

Becerra-Suarez, F. L., Mejia-Cabrera, H. I., Tuesta-Monteza, V. A., & Forero, M. G. (2021). Diagnosis of SARS-CoV-2 Based on Patient Symptoms and Fuzzy Classifiers. In J. A. Lossio-Ventura, J. C. Valverde-Rebaza, E. Díaz, & H. Alatrista-Salas (Eds.), Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings (pp. 484-494). (Communications in Computer and Information Science; Vol. 1410 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-76228-5_35

Becerra-Suarez, Fray L. ; Mejia-Cabrera, Heber I. ; Tuesta-Monteza, Víctor A. et al. / Diagnosis of SARS-CoV-2 Based on Patient Symptoms and Fuzzy Classifiers. Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings. editor / Juan Antonio Lossio-Ventura ; Jorge Carlos Valverde-Rebaza ; Eduardo Díaz ; Hugo Alatrista-Salas. Springer Science and Business Media Deutschland GmbH, 2021. pp. 484-494 (Communications in Computer and Information Science).

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Becerra-Suarez, FL, Mejia-Cabrera, HI, Tuesta-Monteza, VA & Forero, MG 2021, Diagnosis of SARS-CoV-2 Based on Patient Symptoms and Fuzzy Classifiers. in JA Lossio-Ventura, JC Valverde-Rebaza, E Díaz & H Alatrista-Salas (eds), Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings. Communications in Computer and Information Science, vol. 1410 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 484-494, 7th Annual International Conference on Information Management and Big Data, SIMBig 2020, Virtual, Online, 1/10/20. https://doi.org/10.1007/978-3-030-76228-5_35

Diagnosis of SARS-CoV-2 Based on Patient Symptoms and Fuzzy Classifiers. / Becerra-Suarez, Fray L.; Mejia-Cabrera, Heber I.; Tuesta-Monteza, Víctor A. et al.
Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings. ed. / Juan Antonio Lossio-Ventura; Jorge Carlos Valverde-Rebaza; Eduardo Díaz; Hugo Alatrista-Salas. Springer Science and Business Media Deutschland GmbH, 2021. p. 484-494 (Communications in Computer and Information Science; Vol. 1410 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Tuesta-Monteza, Víctor A.

AU - Forero, Manuel G.

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AB - The contention, mitigation and prevention measures that governments have implemented around the world do not appear to be sufficient to prevent the spread of SARS-CoV-2. The number of infected and dead continues to rise every day, putting a strain on the capacity and infrastructure of hospitals and medical centers. Therefore, it is necessary to develop new diagnostic methods based on patients' symptoms that allow the generation of early warnings for appropriate treatment. This paper presents a new method in development for the diagnosis of SARS-CoV-2, based on patient symptoms and the use of fuzzy classifiers. Eleven (11) variables were fuzzified. Then, knowledge rules were established and finally, the center of mass method was used to generate the diagnostic results. The method was tested with a database of clinical records of symptomatic and asymptomatic SARS-CoV-2 patients. By testing the proposed model with data from symptomatic patients, we obtained 100% sensitivity and 100% specificity. Patients according to their symptoms are classified into two classes, allowing for the detection of patients requiring immediate attention from those with milder symptoms.

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Becerra-Suarez FL, Mejia-Cabrera HI, Tuesta-Monteza VA, Forero MG. Diagnosis of SARS-CoV-2 Based on Patient Symptoms and Fuzzy Classifiers. In Lossio-Ventura JA, Valverde-Rebaza JC, Díaz E, Alatrista-Salas H, editors, Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 484-494. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-76228-5_35

Diagnosis of SARS-CoV-2 Based on Patient Symptoms and Fuzzy Classifiers

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Fingerprint

Cite this