Intensive Care Unit Occupancy Time Series Forecasting for COVID-19 Pandemic

Alvaro David Orjuela-Canon, Oscar Perdomo, Leronardo Mendoza, Cesar Hernando Valencia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Nowadays, the pandemic situation because Covid-19 affected everything related to the public health infrastructure. One of the most important aspects to treat the Coronavirus contingency was the hospitalization of patients with severe cases, where some cities had high demand of beds in the intensive care units for attending these people. From the engineering tools, time series forecasting has been an alternative for analyzing data in this context. This work proposes to do a forecasting on the demanded beds for the severe cases of Covid-19, employing models from the artificial intelligence. Techniques as fuzzy and neural networks were tried to determine the necessary number of beds through the use of the registration of this information daily, in a Latin American city. Results show that strategies based on neural networks were better compared to fuzzy models, according to the root mean square error. The obtained models can contribute to the authorities in making decision process to react before the similar contingencies.

Original languageEnglish (US)
Title of host publication2021 IEEE 2nd International Congress of Biomedical Engineering and Bioengineering, CI-IB and BI 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665408554
DOIs
StatePublished - 2021
Event2nd IEEE International Congress of Biomedical Engineering and Bioengineering, CI-IB and BI 2021 - Bogota, Colombia
Duration: Oct 13 2021Oct 15 2021

Publication series

Name2021 IEEE 2nd International Congress of Biomedical Engineering and Bioengineering, CI-IB and BI 2021

Conference

Conference2nd IEEE International Congress of Biomedical Engineering and Bioengineering, CI-IB and BI 2021
Country/TerritoryColombia
CityBogota
Period10/13/2110/15/21

All Science Journal Classification (ASJC) codes

  • Bioengineering
  • Biomedical Engineering
  • Media Technology
  • Orthopedics and Sports Medicine

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