This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
Research Article
Renato Hidaka Torres
UFPA
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
COVID-19 disease has become an unprecedented public health crisis. Although a relatively small percentage of people require intensive care, due to the high degree of contagion of the disease, the public system quickly collapses. Due to the highly complex nature of this disease and variation in its behavior depending on the characteristics of each geographic region, in this work, we analyze data from the Amazon region in Brazil (Pará). We applied several machine learning models to forecast the contagious curve to up 10 days. The Linear SVM and Multilayer Perceptron presented the best overall performances. Until the discovery of a vaccine, every effort is needed to understand and anticipate this disease.
Keywords
machine learning, forecasting, hypothesis test, COVID-19
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
The full text of this article is available to read as a PDF.
Loading...
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 25 Jun, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Artificial Intelligence and Machine Learning
Learn more about our company.
A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research Article
Renato Hidaka Torres
UFPA
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 25 Jun, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Artificial Intelligence and Machine Learning
License:
This work is licensed under a CC BY 4.0 License. Read Full License
COVID-19 disease has become an unprecedented public health crisis. Although a relatively small percentage of people require intensive care, due to the high degree of contagion of the disease, the public system quickly collapses. Due to the highly complex nature of this disease and variation in its behavior depending on the characteristics of each geographic region, in this work, we analyze data from the Amazon region in Brazil (Pará). We applied several machine learning models to forecast the contagious curve to up 10 days. The Linear SVM and Multilayer Perceptron presented the best overall performances. Until the discovery of a vaccine, every effort is needed to understand and anticipate this disease.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
The full text of this article is available to read as a PDF.
Loading...