AIMC Topic: Dengue

Clear Filters Showing 1 to 10 of 66 articles

Functional dynamics between resident transcriptionally active microbes (TAMs) and host genes underlie Dengue severity.

PLoS neglected tropical diseases
Host-microbe interactions are increasingly recognized as an important module to understand disease progression and potential treatment strategies. Increasing evidence points to the microbiome's ability to modulate host gene expression, and thereby in...

Integrating machine learning and time-to-event models to explain and predict risk of hospitalization due to dengue in Colombia.

Scientific reports
Arboviral diseases such as dengue pose major public health challenges in endemic regions, notably in Norte de Santander (Colombia), where they place substantial pressure on healthcare services. We analyzed 8,814 confirmed dengue cases reported to the...

Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables.

Scientific reports
Effective prediction of Aedes mosquito abundance and dengue risk indicators such as the Aedes Index (AI) and Dengue Positive Trap Index (DPTI) is essential for early intervention and targeted vector control. However, current models often rely on coar...

A comparative evaluation of multiple machine learning approaches for forecasting dengue outbreaks in Bangladesh.

Scientific reports
This study aims to forecast dengue incidence in Bangladesh by applying and comparing machine learning techniques. Dengue surveillance data from January 1, 2022, to December 1, 2023, for five divisions of Bangladesh was obtained from the Directorate G...

Comparative estimation of the spread of acute diarrhea and dengue in India using statistical mathematical and deep learning models.

Scientific reports
This study aims to forecast the spread of acute diarrhoea and dengue diseases in India by conducting a comparative analysis of statistical, mathematical (compartmental), and deep learning time series models. Utilizing weekly reported cases and fatali...

Machine-learning-based artificial intelligence tools for the diagnosis of tropical fevers: a systematic review and meta-analysis protocol of diagnostic test accuracy.

BMJ open
INTRODUCTION: Recent advancements in diagnosing tropical fevers increasingly use artificial intelligence (AI). These innovations focus on diagnosing single or multiple diseases, significantly reducing the global burden of tropical fevers. This protoc...

Bridging the predictive divide: A hybrid early warning system for scalable and real-time dengue surveillance in LMICs.

Acta tropica
The global resurgence of dengue presents an ongoing challenge for public health systems, particularly in low- and middle-income countries (LMICs) where conventional early warning systems (EWS) often suffer from reporting delays and under-detection. W...

The role of artificial intelligence for dengue prevention, control, and management: A technical narrative review.

Acta tropica
Dengue fever remains a significant global health threat, particularly in tropical and subtropical regions, where rapid urbanization and climate variability exacerbate its spread. Traditional surveillance and control systems often struggle with delaye...

Discrimination of Dengue Diseases in Children Using Surface-Enhanced Raman Spectroscopy Coupled with Machine Learning Approaches.

Analytical chemistry
This study introduces a novel approach to dengue diagnostics by leveraging surface-enhanced Raman spectroscopy (SERS) coupled to machine learning. This method addresses the critical need for rapid and accurate identification of dengue virus (DENV) in...

SPR-based refractive index sensor design with grated Au-ZnS for dengue detection using machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this paper, we propose a Surface Plasmon Resonance (SPR) fiber optic refractive index (RI) sensor. It consists of a multi-mode fiber (MMF) sensor with a bi-metallic nanostructure with Gold (Au) and Zinc Sulphide (ZnS) as the plasmonic sensing laye...