AI Medical Compendium Topic

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Dengue

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Why Mathematical Computer Simulations Are the New Laboratory for Scientists.

Substance use & misuse
In this paper, we introduce a new powerful scientific paradigm to understand natural and cultural processes. This new paradigm is based on two fundamental keywords: Data, as representative sample of the process we need to analyze, and Artificial Adap...

Describing the breakbone fever: IDODEN, an ontology for dengue fever.

PLoS neglected tropical diseases
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 ...

Artificial Neural Network Analysis of Pharmacokinetic and Toxicity Properties of Lead Molecules for Dengue Fever, Tuberculosis and Malaria.

Current computer-aided drug design
Poor pharmacokinetic and toxicity profiles are major reasons for the low rate of advancing lead drug candidates into efficacy studies. The In-silico prediction of primary pharmacokinetic and toxicity properties in the drug discovery and development p...

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
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...

Developing a dengue forecast model using machine learning: A case study in China.

PLoS neglected tropical diseases
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...

Dengue forecasting in São Paulo city with generalized additive models, artificial neural networks and seasonal autoregressive integrated moving average models.

PloS one
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
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...

Modeling Dengue vector population using remotely sensed data and machine learning.

Acta tropica
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...

Characterization of clinical patterns of dengue patients using an unsupervised machine learning approach.

BMC infectious diseases
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 ...

Exploring single-cell data with deep multitasking neural networks.

Nature methods
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...