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Dengue

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Water tank and swimming pool detection based on remote sensing and deep learning: Relationship with socioeconomic level and applications in dengue control.

PloS one
Studies have shown that areas with lower socioeconomic standings are often more vulnerable to dengue and similar deadly diseases that can be spread through mosquitoes. This study aims to detect water tanks installed on rooftops and swimming pools in ...

Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time.

Scientific reports
Classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using har...

Dengue models based on machine learning techniques: A systematic literature review.

Artificial intelligence in medicine
BACKGROUND: Dengue modeling is a research topic that has increased in recent years. Early prediction and decision-making are key factors to control dengue. This Systematic Literature Review (SLR) analyzes three modeling approaches of dengue: diagnost...

A computational framework to solve the nonlinear dengue fever SIR system.

Computer methods in biomechanics and biomedical engineering
This study is relevant to present the numerical form of the nonlinear dengue fever SIR system are presented using the artificial neural networks along with the Levenberg-Marquardt backpropagation technique, i.e. ANNs-LMB. The procedures of ANNs-LMB a...

Deep learning models for forecasting dengue fever based on climate data in Vietnam.

PLoS neglected tropical diseases
BACKGROUND: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to clima...

Forecasting Weekly Dengue Cases by Integrating Google Earth Engine-Based Risk Predictor Generation and Google Colab-Based Deep Learning Modeling in Fortaleza and the Federal District, Brazil.

International journal of environmental research and public health
Efficient and accurate dengue risk prediction is an important basis for dengue prevention and control, which faces challenges, such as downloading and processing multi-source data to generate risk predictors and consuming significant time and computa...

A Deep Learning Approach for Dengue Fever Prediction in Malaysia Using LSTM with Spatial Attention.

International journal of environmental research and public health
This research aims to predict dengue fever cases in Malaysia using machine learning techniques. A dataset consisting of weekly dengue cases at the state level in Malaysia from 2010 to 2016 was obtained from the Malaysia Open Data website and includes...

Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data.

Scientific reports
Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. Previous work has focused only on specific weather variables and algorithms, and there is still a need...

Meteorological factors cannot be ignored in machine learning-based methods for predicting dengue, a systematic review.

International journal of biometeorology
In recent years, there has been a rapid increase in the application of machine learning methods about predicting the incidence of dengue fever. However, the predictive factors and models employed in different studies vary greatly. Hence, we conducted...

Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data.

International journal of biometeorology
In 2022, Mexico registered an increase in dengue cases compared to the previous year. On the other hand, the amount of precipitation reported annually was slightly less than the previous year. Similarly, the minimum-mean-maximum temperatures recorded...