Version 1
: Received: 15 December 2022 / Approved: 19 December 2022 / Online: 19 December 2022 (08:42:28 CET)
How to cite:
Acosta-Velasquez, R.; Fajardo-Moreno, W.; Espinosa-Leal, L. Predicting Intensive Care Unit Admission of COVID-19 Patients with Open Data: Analysis of the First Wave in Colombia. Preprints2022, 2022120330. https://doi.org/10.20944/preprints202212.0330.v1
Acosta-Velasquez, R.; Fajardo-Moreno, W.; Espinosa-Leal, L. Predicting Intensive Care Unit Admission of COVID-19 Patients with Open Data: Analysis of the First Wave in Colombia. Preprints 2022, 2022120330. https://doi.org/10.20944/preprints202212.0330.v1
Acosta-Velasquez, R.; Fajardo-Moreno, W.; Espinosa-Leal, L. Predicting Intensive Care Unit Admission of COVID-19 Patients with Open Data: Analysis of the First Wave in Colombia. Preprints2022, 2022120330. https://doi.org/10.20944/preprints202212.0330.v1
APA Style
Acosta-Velasquez, R., Fajardo-Moreno, W., & Espinosa-Leal, L. (2022). Predicting Intensive Care Unit Admission of COVID-19 Patients with Open Data: Analysis of the First Wave in Colombia. Preprints. https://doi.org/10.20944/preprints202212.0330.v1
Chicago/Turabian Style
Acosta-Velasquez, R., William Fajardo-Moreno and Leonardo Espinosa-Leal. 2022 "Predicting Intensive Care Unit Admission of COVID-19 Patients with Open Data: Analysis of the First Wave in Colombia" Preprints. https://doi.org/10.20944/preprints202212.0330.v1
Abstract
Optimizing intensive care resources using predicting modeling is paramount for fighting the COVID-19 pandemic. In this paper, we model the admission of COVID-19 patients in intensive care units (ICU) in Colombia using openly available data gathered from 18 March 2020 to 14 October 2020. After an intensive preprocessing of the data, we trained four different machine learning models using four different strategies for handling the imbalanced features. Our findings show that our best model (XGBoost) effectively predicts an Area Under the Curve (AUC-ROC) of 0.94, in line with the state-of-the-art results obtained in other predictive models obtained with medical data.
Keywords
Covid-19; machine learnin;, ICU; admission
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
