Prediction of mortality due to Covid 19 in Peru using artificial neural networks
Abstract
With the development of the pandemic in Peru, the number of deaths has been increasing and unfortunately the appropriate measures have not been taken, this because we do not have a tool that allows us to know the number of possible deaths in a given time. The objective of this article is to propose a tool capable of predicting the number of deaths from COVID-19 as a function of time. The methodology used was artificial neural networks using time series with information obtained from the Ministry of Health of the Peruvian state through its open data portal. The results achieved had a mean square error of 0.0037 and a loss of 0.0480. The results obtained throughout the article confirm the validity of this tool and its effectiveness in predicting the number of deaths from COVID 19.
Downloads
References
Organización Mundial de la Salud, “coronavirus COVID 19” July, 2021. [Online]. Available: https://www.who.int/es/emergencies/diseases/novel-coronavirus-2019?gclid=CjwKCAjw55-HBhAHEiwARMCszrbbBSFmekHH9cphVjelvC85L8pGGpKMcOMiNDkbJPAMYeUrpSEXaRoCT7MQAvD_BwE. [Accessed Jul. 09, 2021].
Ministerio de salud, “datos abiertos,” July, 2021. [Online]. Available: https://www.datosabiertos.gob.pe/dataset/fallecidos-por-covid-19-ministerio-de-salud-minsa/resource/4b7636f3-5f0c-4404-8526. [Accessed Jul. 09, 2021].
R. Pino, A. Gómez, N.de Abajo, "Introducción a la inteligencia artificial: sistemas expertos, redes neuronales artificiales y computación evolutiva," Universidad de Oviedo, pp. 01, 2001.
C. Guisande, A. Vaamonde, A. Barreiro, "Tratamiento de datos con R, Statistica y SPSS," Ediciones Diaz de santos, pp. 585, 2013.
J. Arnau, "Diseños de Series Temporales: Técnicas de Análisis," Edicions Universitat Barcelona, pp. 92, 2001.
W. McKinney, "Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython," O'Reilly Media, pp. 04, 2012.
F. Nelli, "Python Data Analytics: With Pandas, NumPy, and Matplotlib," Apress, pp. 47, 2018.
J. Torres, "DEEP LEARNING Introducción práctica con Keras," CC BY-NC-SA, pp. 97, 2018.
B. Auffarth, "Artificial Intelligence with Python Cookbook: Proven recipes for applying AI algorithms and deep learning techniques using TensorFlow 2.x and PyTorch 1.6," Packt Publishing Ltd, pp. 10, 2020.
- Conceptualization
- Data curation
- Formal Analysis
- Investigation
- Methodology
- Validation
- Writing - original draft
- Conceptualization
- Data curation
- Formal Analysis
- Investigation
- Methodology
- Software
- Validation
- Writing - original draft
- Conceptualization
- Data curation
- Formal Analysis
- Investigation
- Methodology
- Software
- Validation
- Writing - original draft
Copyright (c) 2021 Innovation and Software
This work is licensed under a Creative Commons Attribution 4.0 International License.
The authors exclusively grant the right to publish their article to the Innovation and Software Journal, which may formally edit or modify the approved text to comply with their own editorial standards and with universal grammatical standards, prior to publication; Likewise, our journal may translate the approved manuscripts into as many languages as it deems necessary and disseminates them in several countries, always giving public recognition to the author or authors of the research.
