Do not forget interaction: Predicting fatality of COVID-19 patients
using logistic regression
- URL: http://arxiv.org/abs/2006.16942v1
- Date: Tue, 30 Jun 2020 16:28:41 GMT
- Title: Do not forget interaction: Predicting fatality of COVID-19 patients
using logistic regression
- Authors: Feng Zhou, Tao Chen, and Baiying Lei
- Abstract summary: We reported an explainable, intuitive, and accurate machine learning model based on logistic regression to predict the fatality rate of COVID-19 patients.
We found that when the fatality probability produced by the logistic regression model was over 0.8, the model had the optimal performance in that it was able to predict patient fatalities more than 11.30 days on average with maximally 34.91 days in advance.
Such a model can be used to identify COVID-19 patients with high risks with three blood biomarkers and help the medical systems around the world plan critical medical resources amid this pandemic.
- Score: 20.591050444038714
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Amid the ongoing COVID-19 pandemic, whether COVID-19 patients with high risks
can be recovered or not depends, to a large extent, on how early they will be
treated appropriately before irreversible consequences are caused to the
patients by the virus. In this research, we reported an explainable, intuitive,
and accurate machine learning model based on logistic regression to predict the
fatality rate of COVID-19 patients using only three important blood biomarkers,
including lactic dehydrogenase, lymphocyte (%) and high-sensitivity C-reactive
protein, and their interactions. We found that when the fatality probability
produced by the logistic regression model was over 0.8, the model had the
optimal performance in that it was able to predict patient fatalities more than
11.30 days on average with maximally 34.91 days in advance, an accumulative
f1-score of 93.76% and and an accumulative accuracy score of 93.92%. Such a
model can be used to identify COVID-19 patients with high risks with three
blood biomarkers and help the medical systems around the world plan critical
medical resources amid this pandemic.
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