AIMC Topic: Dengue
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Exploring single-cell data with deep multitasking neural networks.
Nature methods
Oct 7, 2019
It is currently challenging to analyze single-cell data consisting of many cells and samples, and to address variations arising from batch effects and different sample preparations. For this purpose, we present SAUCIE, a deep neural network that comb...
Characterization of clinical patterns of dengue patients using an unsupervised machine learning approach.
BMC infectious diseases
Jul 22, 2019
BACKGROUND: Despite the greater sensitivity of the new dengue clinical classification proposed by the World Health Organization (WHO) in 2009, there is a need for a better definition of warning signs and clinical progression of dengue cases. Classic ...
Modeling Dengue vector population using remotely sensed data and machine learning.
Acta tropica
May 16, 2018
Mosquitoes are vectors of many human diseases. In particular, Aedes ægypti (Linnaeus) is the main vector for Chikungunya, Dengue, and Zika viruses in Latin America and it represents a global threat. Public health policies that aim at combating this v...
Dengue forecasting in São Paulo city with generalized additive models, artificial neural networks and seasonal autoregressive integrated moving average models.
PloS one
Apr 2, 2018
Globally, the number of dengue cases has been on the increase since 1990 and this trend has also been found in Brazil and its most populated city-São Paulo. Surveillance systems based on predictions allow for timely decision making processes, and in ...
The utility of LASSO-based models for real time forecasts of endemic infectious diseases: A cross country comparison.
Journal of biomedical informatics
Feb 27, 2018
INTRODUCTION: Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control methods at an early stage of disease outbreaks. Climatic variables has been identified as important pre...
Humans
Machine Learning
Chickenpox
Models, Statistical
Taiwan
Singapore
Malaria
Dengue
Japan
Infectious Disease Medicine
Climate
Hand, Foot and Mouth Disease
Wavelet Analysis
Public Health
Algorithms
Communicable Disease Control
Disease Outbreaks
Thailand
Forecasting
Incidence
Communicable Diseases
Reproducibility of Results
Developing a dengue forecast model using machine learning: A case study in China.
PLoS neglected tropical diseases
Oct 16, 2017
BACKGROUND: In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine lea...
Quantum associative memory with linear and non-linear algorithms for the diagnosis of some tropical diseases.
Neural networks : the official journal of the International Neural Network Society
Sep 21, 2017
This paper presents the QAMDiagnos, a model of Quantum Associative Memory (QAM) that can be a helpful tool for medical staff without experience or laboratory facilities, for the diagnosis of four tropical diseases (malaria, typhoid fever, yellow feve...
Describing the breakbone fever: IDODEN, an ontology for dengue fever.
PLoS neglected tropical diseases
Feb 3, 2015
BACKGROUND: Ontologies represent powerful tools in information technology because they enhance interoperability and facilitate, among other things, the construction of optimized search engines. To address the need to expand the toolbox available for ...
Risk Stratification of Dengue Cases Requiring Hospitalization.
Journal of medical virology
Aug 1, 2025
Dengue pathogenesis involves immune-driven inflammation that contributes to severe disease progression. This study assessed a machine learning model to identify a minimal, yet highly predictive biomarker set, aiming to support clinical decision-makin...
A high-resolution GIS and machine learning approach for targeted disease management and localized risk assessment in an urban setup: A case study from Bhopal, Central India.
Acta tropica
Jul 1, 2025
Predicting dengue distribution based on environmental factors is crucial for effective vector control and management as environmental factors like temperature, demographics, and artificial changes such as roads and buildings significantly influence d...
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