[HTML][HTML] Design of an artificial neural network to predict mortality among COVID-19 patients
M Shanbehzadeh, R Nopour… - Informatics in medicine …, 2022 - Elsevier
Introduction The fast pandemic of coronavirus disease 2019 (COVID-19) has challenged
clinicians with many uncertainties and ambiguities regarding disease outcomes and …
clinicians with many uncertainties and ambiguities regarding disease outcomes and …
Developing an artificial neural network for detecting COVID-19 disease
M Shanbehzadeh, R Nopour… - Journal of education …, 2022 - journals.lww.com
BACKGROUND: From December 2019, atypical pneumonia termed COVID-19 has been
increasing exponentially across the world. It poses a great threat and challenge to world …
increasing exponentially across the world. It poses a great threat and challenge to world …
A new interval type-2 fuzzy aggregation approach for combining multiple neural networks in clustering and prediction of time series
M Ramírez, P Melin - International Journal of Fuzzy Systems, 2023 - Springer
Inspired by how some cognitive abilities affect the human decision-making process, the
proposed approach combines neural networks with type-2 fuzzy systems. The proposal …
proposed approach combines neural networks with type-2 fuzzy systems. The proposal …
[PDF][PDF] GA-optimized multivariate CNN-LSTM model for predicting multi-channel mobility in the COVID-19 pandemic
H Widiputra - Emerging Science Journal, 2021 - researchgate.net
The primary factor that contributes to the transmission of COVID-19 infection is human
mobility. Positive instances added on a daily basis have a substantial positive association …
mobility. Positive instances added on a daily basis have a substantial positive association …
[HTML][HTML] Predicting risk of mortality in COVID-19 hospitalized patients using hybrid machine learning algorithms
MR Afrash, M Shanbehzadeh… - Journal of biomedical …, 2022 - ncbi.nlm.nih.gov
Background: Since hospitalized patients with COVID-19 are considered at high risk of death,
the patients with the sever clinical condition should be identified. Despite the potential of …
the patients with the sever clinical condition should be identified. Despite the potential of …
[PDF][PDF] GA-Stacking: A New Stacking-Based Ensemble Learning Method to Forecast the COVID-19 Outbreak.
WN Ismail, HA Alsalamah… - Computers, Materials & …, 2023 - cdn.techscience.cn
As a result of the increased number of COVID-19 cases, Ensemble Machine Learning (EML)
would be an effective tool for combatting this pandemic outbreak. An ensemble of classifiers …
would be an effective tool for combatting this pandemic outbreak. An ensemble of classifiers …
[HTML][HTML] Development of an intelligent clinical decision support system for the early prediction of diabetic nephropathy
Background Diabetic nephropathy (DN) is the most common microvascular complication of
diabetes mellitus (DM) and is identified as a leading cause of the end-stage renal disease …
diabetes mellitus (DM) and is identified as a leading cause of the end-stage renal disease …
Classification of Consumption Level in Developing Countries for Time Series Prediction Using a Hierarchical Nested Artificial Neural Network Method
M Ramirez, P Melin - New Horizons for Fuzzy Logic, Neural Networks and …, 2024 - Springer
A significant factor in the negative impact of the operation of a developing country is the
change in global economic conditions, combined with the possibility of the materialization of …
change in global economic conditions, combined with the possibility of the materialization of …
Development of an intelligent clinical decision support system for the early prediction of diabetic nephropathy
M RezaAfrash, F Rahim, M Shanbezadeh… - Informatics in Medicine …, 2023 - eprints.lums.ac.ir
Background Diabetic nephropathy (DN) is the most common microvascular complication of
diabetes mellitus (DM) and is identified as a leading cause of the end-stage renal disease …
diabetes mellitus (DM) and is identified as a leading cause of the end-stage renal disease …
Introduction to Prediction with Neural Networks
P Melin, M Ramirez, O Castillo - … , and Time Series Prediction by Using …, 2024 - Springer
The human being can solve multiple problems simultaneously using different parts of the
brain, which by itself represents a complex subject of study. For several decades, a great …
brain, which by itself represents a complex subject of study. For several decades, a great …