Abolfazl Mollalo
Biographic Data
| ID | 7930747 |
|---|---|
| NAME | Abolfazl Mollalo |
| GIVEN NAMES | Abolfazl |
| FAMILY NAME | Mollalo |
| SIGNATURE | MOLLALO A |
| AFFILIATIONS | Baldwin Wallace University |
| ORCID | 0000-0001-5092-0698 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Spatial Modeling of Covid-19 Prevalence Using Adaptive Neuro-Fuzzy Inference System
This study is dedicated to modeling the spatial variation in COVID-19 prevalence using the adaptive neuro-fuzzy inference system (ANFIS) when dealing with nonlinear relationships, especially useful for small areas or small sample size problems. We compiled a broad range of socio-demographic, environmental, and climatic factors along with potentially related urban land uses to predict COVID-19 prevalence in rural districts of the Golestan province…
Spatial statistical analysis of pre-existing mortalities of 20 diseases with Covid-19 mortalities in the continental United States
Spatial Modeling of Covid-19 Vaccine Hesitancy in the United States
Vaccine hesitancy refers to delay in acceptance or refusal of vaccines despite the availability of vaccine services. Despite the efforts of United States healthcare providers to vaccinate the bulk of its population, vaccine hesitancy is still a severe challenge that has led to the resurgence of COVID-19 cases to over 100,000 people during early August 2021. To our knowledge, there are limited nationwide studies that examined the spatial distribut…
GIS-based spatial modeling of Covid-19 incidence rate in the continental United States
Artificial Neural Network Modeling of Novel Coronavirus (Covid-19) Incidence Rates across the Continental United States
Prediction of the COVID-19 incidence rate is a matter of global importance, particularly in the United States. As of 4 June 2020, more than 1.8 million confirmed cases and over 108 thousand deaths have been reported in this country. Few studies have examined nationwide modeling of COVID-19 incidence in the United States particularly using machine-learning algorithms. Thus, we collected and prepared a database of 57 candidate explanatory variables…
A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States
Despite the usefulness of artificial neural networks (ANNs) in the study of various complex problems, ANNs have not been applied for modeling the geographic distribution of tuberculosis (TB) in the US. Likewise, ecological level researches on TB incidence rate at the national level are inadequate for epidemiologic inferences. We collected 278 exploratory variables including environmental and a broad range of socio-economic features for modeling t…
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A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States
Despite the usefulness of artificial neural networks (ANNs) in the study of various complex problems, ANNs have not been applied for modeling the geographic distribution of tuberculosis (TB) in the US. Likewise, ecological level researches on TB incidence rate at the national level are inadequate for epidemiologic inferences. We collected 278 exploratory variables including environmental and a broad range of socio-economic features for modeling t…
GIS-based spatial modeling of Covid-19 incidence rate in the continental United States
Artificial Neural Network Modeling of Novel Coronavirus (Covid-19) Incidence Rates across the Continental United States
Prediction of the COVID-19 incidence rate is a matter of global importance, particularly in the United States. As of 4 June 2020, more than 1.8 million confirmed cases and over 108 thousand deaths have been reported in this country. Few studies have examined nationwide modeling of COVID-19 incidence in the United States particularly using machine-learning algorithms. Thus, we collected and prepared a database of 57 candidate explanatory variables…
Spatial statistical analysis of pre-existing mortalities of 20 diseases with Covid-19 mortalities in the continental United States
Spatial Modeling of Covid-19 Vaccine Hesitancy in the United States
Vaccine hesitancy refers to delay in acceptance or refusal of vaccines despite the availability of vaccine services. Despite the efforts of United States healthcare providers to vaccinate the bulk of its population, vaccine hesitancy is still a severe challenge that has led to the resurgence of COVID-19 cases to over 100,000 people during early August 2021. To our knowledge, there are limited nationwide studies that examined the spatial distribut…
Spatial Modeling of Covid-19 Prevalence Using Adaptive Neuro-Fuzzy Inference System
This study is dedicated to modeling the spatial variation in COVID-19 prevalence using the adaptive neuro-fuzzy inference system (ANFIS) when dealing with nonlinear relationships, especially useful for small areas or small sample size problems. We compiled a broad range of socio-demographic, environmental, and climatic factors along with potentially related urban land uses to predict COVID-19 prevalence in rural districts of the Golestan province…
Medicine (6 works) · COVID-19 epidemiological studies (5 works) · Environmental health (5 works) · Geography (5 works) · Population (5 works) · Demography (4 works) · Mathematics (4 works) · Statistics (4 works) · Data-Driven Disease Surveillance (3 works) · Disease (3 works)