AIMC Topic: Dengue
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Forecasting invasive mosquito abundance in the Basque Country, Spain using machine learning techniques.
Parasites & vectors
Mar 15, 2025
BACKGROUND: Mosquito-borne diseases cause millions of deaths each year and are increasingly spreading from tropical and subtropical regions into temperate zones, posing significant public health risks. In the Basque Country region of Spain, changing ...
Circulating lncRNAs as biomarkers for severe dengue using a machine learning approach.
The Journal of infection
Mar 14, 2025
OBJECTIVES: Dengue virus (DENV) infection is a significant global health concern, causing severe morbidity and mortality. While many cases present as a mild febrile illness, some progress to life-threatening severe dengue (SD). Early intervention is ...
Forecasting dengue across Brazil with LSTM neural networks and SHAP-driven lagged climate and spatial effects.
BMC public health
Mar 12, 2025
BACKGROUND: Dengue fever is a mosquito-borne viral disease that poses significant health risks and socioeconomic challenges in Brazil, necessitating accurate forecasting across its 27 federal states. With the country's diverse climate and geographica...
Machine learning for predicting severe dengue in Puerto Rico.
Infectious diseases of poverty
Feb 4, 2025
BACKGROUND: Distinguishing between non-severe and severe dengue is crucial for timely intervention and reducing morbidity and mortality. World Health Organization (WHO)-recommended warning signs offer a practical approach for clinicians but have limi...
Leveraging AHP and transfer learning in machine learning for improved prediction of infectious disease outbreaks.
Scientific reports
Dec 31, 2024
Infectious diseases significantly impact both public health and economic stability, underscoring the critical need for precise outbreak predictions to effictively mitigate their impact. This study applies advanced machine learning techniques to forec...
Modeling and analysis of dengue transmission in fuzzy-fractional framework: a hybrid residual power series approach.
Scientific reports
Dec 28, 2024
The current manuscript presents a mathematical model of dengue fever transmission with an asymptomatic compartment to capture infection dynamics in the presence of uncertainty. The model is fuzzified using triangular fuzzy numbers (TFNs) approach. Th...
Predicting the infecting dengue serotype from antibody titre data using machine learning.
PLoS computational biology
Dec 23, 2024
The development of a safe and efficacious vaccine that provides immunity against all four dengue virus serotypes is a priority, and a significant challenge for vaccine development has been defining and measuring serotype-specific outcomes and correla...
Severity prediction markers in dengue: a prospective cohort study using machine learning approach.
Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals
Nov 28, 2024
BACKGROUND: Dengue virus causes illnesses with or without warning indicators for severe complications. There are no clear prognostic signs linked to the disease outcomes.
Smart monitoring solution for dengue infection control: A digital twin-inspired approach.
Computer methods and programs in biomedicine
Oct 10, 2024
BACKGROUND AND OBJECTIVE: In the realm of smart healthcare, precise monitoring and prediction services are crucial for mitigating the impact of infectious diseases. This study introduces an innovative digital twin technology-inspired monitoring archi...
The fuzzy system ensembles entomological, epidemiological, demographic and environmental data to unravel the dengue transmission risk in an endemic city.
BMC public health
Sep 27, 2024
BACKGROUND: The effectiveness of dengue control interventions depends on an effective integrated surveillance system that involves analysis of multiple variables associated with the natural history and transmission dynamics of this arbovirus. Entomol...
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