A systematic review of dengue outbreak prediction models: Current scenario and future directions
Dengue is among the fastest-spreading vector-borne infectious disease, with outbreaks
often overwhelm the health system and result in huge morbidity and mortality in its endemic …
often overwhelm the health system and result in huge morbidity and mortality in its endemic …
Big geospatial data and data-driven methods for urban dengue risk forecasting: a review
With advancements in big geospatial data and artificial intelligence, multi-source data and
diverse data-driven methods have become common in dengue risk prediction …
diverse data-driven methods have become common in dengue risk prediction …
Prediction of dengue incidents using hospitalized patients, metrological and socio-economic data in Bangladesh: A machine learning approach
Dengue fever is a severe disease spread by Aedes mosquito-borne dengue viruses
(DENVs) in tropical areas such as Bangladesh. Since its breakout in the 1960s, dengue …
(DENVs) in tropical areas such as Bangladesh. Since its breakout in the 1960s, dengue …
A reproducible ensemble machine learning approach to forecast dengue outbreaks
Dengue fever, a prevalent and rapidly spreading arboviral disease, poses substantial public
health and economic challenges in tropical and sub-tropical regions worldwide. Predicting …
health and economic challenges in tropical and sub-tropical regions worldwide. Predicting …
How heterogeneous is the dengue transmission profile in Brazil? A study in six Brazilian states
IF de Almeida, RM Lana… - PLoS neglected tropical …, 2022 - journals.plos.org
Dengue is a vector-borne disease present in most tropical countries, infecting an average of
50 to 100 million people per year. Socioeconomic, demographic, and environmental factors …
50 to 100 million people per year. Socioeconomic, demographic, and environmental factors …
Improving dengue forecasts by using geospatial big data analysis in google earth engine and the historical dengue information-aided long short term memory …
Simple Summary Forecasting dengue cases often face challenges from (1) time-
effectiveness due to time-consuming satellite data downloading and processing,(2) weak …
effectiveness due to time-consuming satellite data downloading and processing,(2) weak …
AI-based epidemic and pandemic early warning systems: A systematic sco** review
C El Morr, D Ozdemir, Y Asdaah… - Health Informatics …, 2024 - journals.sagepub.com
Background: Timely detection of disease outbreaks is critical in public health. Artificial
Intelligence (AI) can identify patterns in data that signal the onset of epidemics and …
Intelligence (AI) can identify patterns in data that signal the onset of epidemics and …
Meteorological factors cannot be ignored in machine learning-based methods for predicting dengue, a systematic review
L Fang, W Hu, G Pan - International Journal of Biometeorology, 2024 - Springer
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 …
methods about predicting the incidence of dengue fever. However, the predictive factors and …
Forecasting weekly dengue cases by integrating google earth engine-based risk predictor generation and google colab-based deep learning modeling in fortaleza …
Z Li - International journal of environmental research and …, 2022 - mdpi.com
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 …
and control, which faces challenges, such as downloading and processing multi-source data …
Predicting dengue outbreaks with explainable machine learning
Seasonal infectious diseases, such as dengue, have been causing great losses in many
countries around the world in terms of deaths, quality of life, and economic burden. In Brazil …
countries around the world in terms of deaths, quality of life, and economic burden. In Brazil …