ArticleNonlinear dynamics2021
Comparison of an artificial neural network and Gompertz model for predicting the dynamics of deaths from COVID-19 in México.
Article in Nonlinear dynamics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Optimal resource allocation model for COVID-19: a systematic review and meta-analysis.BMC infectious diseases · 2024Pooled it
- A multi-method study evaluating the inference of compartmental model parameters from a generative agent-based model.Infectious Disease Modelling · 2026Article
- Climate and COVID-19 transmission: a cross-sectional study in Africa.Scientific reports · 2023Article
- Forecasting COVID-19 spreading through an ensemble of classical and machine learning models: Spain's case study.Scientific reports · 2023Article
- Deep Spatio-Temporal Graph Network with Self-Optimization for Air Quality Prediction.Entropy (Basel, Switzerland) · 2023Article
- Comparing artificial neural network training algorithms to predict length of stay in hospitalized patients with COVID-19.BMC infectious diseases · 2022Article
- Relationship between Shale Hydration and Shale Collapse.ACS omega · 2022Article
- Stochastic forecasting of COVID-19 daily new cases across countries with a novel hybrid time series model.Nonlinear dynamics · 2022Article
- Forecast of the outbreak of COVID-19 using artificial neural network: Case study Qatar, Spain, and Italy.Results in physics · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The present work is focused on modeling and predicting the cumulative number of deaths from COVID-19 in México by comparing an artificial neural network (ANN) with a Gompertz model applying multiple optimization algorithms for the estimation of coefficients and parameters, respectively. For the modeling process, the data published by the daily technical report COVID-19 in Mexico from March 19th to September 30th were used. The data published in the month of October were included to carry out the prediction. The results show a satisfactory comparison between the real data and those obtained by both models with a R
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Registered trials
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