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Use of Artificial Intelligence Techniques in the Prediction of the Pre and Asymptomatic Patient to COVID-19
26 Pages Posted: 11 Sep 2020More...
Background: Current epidemiological studies are based, mainly, on tools that analyze the contagions of COVID 19 that happened in different regions, thus causing a reactive action in the decision-making processes of the different actors of the global health system in coping with the disease.
Methods: The proposed new methodology is based on data processing, linking artificial intelligence techniques based on multivariate statistical concepts, with different clustering methods applied to the pathologies of epidemiological diseases, mainly targeting COVID-19. Another concept used for cross-correlation of data refers to the stability of a given process, applying to the measured vital signs of citizens on a semi-continuous and periodic basis.
Findings: The correlation between the tendency of vital signs instability and pathologies allows the identification of the different profiles of diseases present or incubated in individuals, and health conditions as potentiators in the severity of the disease. The system created in massive epidemiological monitoring, geo locates areas with asymptomatic patients, with potential for transmission.
Interpretation: The methodology is proposed as a tool to support the decision-making processes of public health systems, allowing actions of social isolation in a selective way and control of the dissemination of Sars-Cov-2.
Funding: No funding source.
Declaration of Interests: None declared.
Ethics Approval Statement: The work has informed consent by the university's Research Ethics Committee, as well as online acceptance of the informed consent form (ICF) by the participating volunteers.
Keywords: asymptomatic patients; Covid 19; Predictive epidemiology
Suggested Citation: Suggested Citation