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Use of Classification Techniques for the Analysis of Data Related to COVID-19 in México
2nd International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2022 ; 1675 CCIS:524-534, 2022.
Article in English | Scopus | ID: covidwho-2173759
ABSTRACT
SARS-CoV-2 has bought many challenges to the world, socially, economically, and healthy habits. Even to those that have not experienced the sickness itself, and even though it has changed the lifestyle of the people across the world nation wise the effects of COVID-19 need to be analyzed and understood, analyzing a large amount of data is a process by itself, in this document details the analysis of the data collected from México by the Secretary of Health, the data was analyzed by implementing statistics, and classification methods known as K-Means, C&R Tree and TwoStep Cluster, using processed and unprocessed data. With the main emphasis on K-means. The study has the purpose of detecting what makes the highest impact on a person, to get sick, and succumb to the effects of the disease. In the study, it was found that in México the age of risk is at its highest at the age of 57, and the ones at the highest risk of mortality are those with hypertension and obesity, with those that present both at the age of 57 having a 19.37% of death. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2nd International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2nd International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2022 Year: 2022 Document Type: Article