Clustering Proposal Support for the COVID-19 Making Decision Process in a Data Demanding Scenario

A. D. Orjuela-Cañón; Oscar Julian Perdomo Charry

doi:10.1109/TLA.2021.9451250

Clustering Proposal Support for the COVID-19 Making Decision Process in a Data Demanding Scenario

A. D. Orjuela-Cañón
, Oscar Julian Perdomo Charry

Research output: Contribution to specialist publication › Public engagement article

6 Scopus citations

Abstract

The COVID-19 disease surprised the world in the last months due to the number of infections and deaths have been increased in an exponential way. Since the pandemic was established by the World Health Organization, different strategies have been proposed for dealing diverse problems in cities that the coronavirus affected. This work presents a method to decision making support processes, specifically in environment with few data and variables to be considered. Thus, artificial neural networks architectures were employed to cluster the information available in the Bogota city, and provide a tool that allows generating additional findings in a simultaneous mode, and expressed as a visual map. The present proposal reached sensitivity measures around 75%, obtaining 100% for the best cases.

Original language	Spanish (Colombia)
Pages	1041 - 1049
Number of pages	8
Volume	19
No	6
Specialist publication	IEEE Latin America Transactions
DOIs	https://doi.org/10.1109/TLA.2021.9451250
State	Published - Jun 10 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Immunology and Microbiology (miscellaneous)

Access to Document

10.1109/TLA.2021.9451250

Cite this

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title = "Clustering Proposal Support for the COVID-19 Making Decision Process in a Data Demanding Scenario",

abstract = "The COVID-19 disease surprised the world in the last months due to the number of infections and deaths have been increased in an exponential way. Since the pandemic was established by the World Health Organization, different strategies have been proposed for dealing diverse problems in cities that the coronavirus affected. This work presents a method to decision making support processes, specifically in environment with few data and variables to be considered. Thus, artificial neural networks architectures were employed to cluster the information available in the Bogota city, and provide a tool that allows generating additional findings in a simultaneous mode, and expressed as a visual map. The present proposal reached sensitivity measures around 75\%, obtaining 100\% for the best cases.",

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N2 - The COVID-19 disease surprised the world in the last months due to the number of infections and deaths have been increased in an exponential way. Since the pandemic was established by the World Health Organization, different strategies have been proposed for dealing diverse problems in cities that the coronavirus affected. This work presents a method to decision making support processes, specifically in environment with few data and variables to be considered. Thus, artificial neural networks architectures were employed to cluster the information available in the Bogota city, and provide a tool that allows generating additional findings in a simultaneous mode, and expressed as a visual map. The present proposal reached sensitivity measures around 75%, obtaining 100% for the best cases.

AB - The COVID-19 disease surprised the world in the last months due to the number of infections and deaths have been increased in an exponential way. Since the pandemic was established by the World Health Organization, different strategies have been proposed for dealing diverse problems in cities that the coronavirus affected. This work presents a method to decision making support processes, specifically in environment with few data and variables to be considered. Thus, artificial neural networks architectures were employed to cluster the information available in the Bogota city, and provide a tool that allows generating additional findings in a simultaneous mode, and expressed as a visual map. The present proposal reached sensitivity measures around 75%, obtaining 100% for the best cases.

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DO - 10.1109/TLA.2021.9451250

M3 - Artículo de divulgación

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JO - IEEE Latin America Transactions

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