https://github.com/vinicius999/icu-beds-forecast-covid-19

Predição da ocupação de leitos de UTI no Brasil devido a pandemia do COVID-19, usando Support Vector Regression (SVR)
https://github.com/vinicius999/icu-beds-forecast-covid-19

covid-19 matplotlib numpy pandas python sklearn support-vector-regression

Last synced: about 4 hours ago
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Predição da ocupação de leitos de UTI no Brasil devido a pandemia do COVID-19, usando Support Vector Regression (SVR)

• Host: GitHub
• URL: https://github.com/vinicius999/icu-beds-forecast-covid-19
• Owner: Vinicius999
• License: mit
• Created: 2022-09-25T21:00:17.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-11-26T01:18:44.000Z (about 2 years ago)
• Last Synced: 2024-11-13T12:52:17.507Z (2 months ago)
• Topics: covid-19, matplotlib, numpy, pandas, python, sklearn, support-vector-regression
• Language: Python
• Homepage:
• Size: 309 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Prediction of the Occupancy Rate of ICU Beds by COVID-19 in Brazil Using SVR

This study sought to apply the SVR technique to predict the ICU bed occupancy rate by COVID-19 in Brazil for 7, 14, 21 and 28 days after May 10, 2021. See the document [here](https://www.even3.com.br/anais/cobicet/374955-predicao-da-taxa-de-ocupacao-de-leitos-de-uti-por-covid-19-no-brasil-usando-svr/).

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## Tecnologias



    

        

    

	

        

    



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## Data

- Data Source:  https://bigdata-covid19.icict.fiocruz.br/

- Number of instances:  27 instances

- Date of last instance:  10/05/2021 (day / month / year)

- Final data:

  ![Figure](https://github.com/Vinicius999/ICU-beds-forecast-covid-19/blob/main/images/dataset-image.png)

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## Methodology

- Training data:  85%

- Validation data:  15%

- Metric:  MAE (Mean Absolute Error)

- No. of training and validation tests:  10

- Prediction time intervals:  7, 14, 21 and 28 days after the last collection date

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## Results

### Training and validation

Figures 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10 show the graph referring to the training and validation in each testing testing phase, respectively.

![Figure](https://github.com/Vinicius999/ICU-beds-forecast-covid-19/blob/main/images/tests-01-02-05-06.png)

![Figure](https://github.com/Vinicius999/ICU-beds-forecast-covid-19/blob/main/images/tests-03-04-07-08.png)

![Figure](https://github.com/Vinicius999/ICU-beds-forecast-covid-19/blob/main/images/tests-09-10.png)

The table shows the parameters that were changed in each test, as well as the respective MAE results. The parameters `gamma` and `coef0` were constant for all tests, with the values `'auto'` and `1`, respectively.

![Figure](https://github.com/Vinicius999/ICU-beds-forecast-covid-19/blob/main/images/tests-parameters-image.png)

### Prediction

In the testing phase, the parameters used in the 6th test were chosen because of the lowest MAE value obtained (8.80%), so the SVR function was as follows:

`SVR(kernel='poly', C=1, gamma='auto', degree=8, epsilon=0.1, coef0=1)`

The figure below shows the result of this prediction:

![Figure](https://github.com/Vinicius999/ICU-beds-forecast-covid-19/blob/main/images/predict-image.png)

- red dots: actual occupancy rates already available in the dataset;

- blue curve: regression for the already known values

- red curve: prediction of future days

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## Paper

SÁ, Gabriel Caldas Barros e et al. (2021) [Predição Da Taxa de Ocupação de Leitos de UTI Por COVID-19 No Brasil Usando SVR](https://www.even3.com.br/anais/cobicet/374955-predicao-da-taxa-de-ocupacao-de-leitos-de-uti-por-covid-19-no-brasil-usando-svr/).. In: Anais do Congresso Brasileiro Interdisciplinar em Ciência e Tecnologia. Anais...Diamantina(MG) UFVJM.