Pular para o conteúdo principal

ETHNOS_APP

Início • Busca • Periódicos • Lista 0

Maaweya Awadalla

Dados Biográficos

ID8325639
NOMEMaaweya Awadalla
PRENOMESMaaweya
SOBRENOMEAwadalla
ASSINATURAAWADALLA M
AFILIAÇÕESKing Fahd Medical City
ORCID0000-0002-1270-2216
VERIFICADOSim
TOTAL DE OBRAS3
TOTAL DE CITAÇÕES0
TOTAL COMO AUTOR3
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2024
ANO MAIS RECENTE DE PUBLICAÇÃO2026
ÍNDICE H0
  • Early-warning prediction of visceral leishmaniasis mortality using a multivariate STL–deep learning hybrid approach on 20 years of monthly time series

    Open Access•Fathelrhman EL Guma, Maaweya Awadalla et al.•ARTICLE•Frontiers in Public Health•2026

    Introduction Visceral leishmaniasis (VL) is a preventable disease, but continues to cause mortality in Sudan, with transmission dynamics and potentially fatal outcomes strongly affected by local environmental conditions. Methods This research presents an innovative hybrid forecasting framework that amalgamates Seasonal-Trend decomposition using Loess (STL) with four sophisticated models: Gaussian Process Regression (GPR), Long Short-Term Memory (…

  • A hybrid STL–LightGBM framework with probabilistic forecasting for Influenza A incidence in the post-pandemic Saudi Arabia

    Open Access•Reham M Alahmadi, Maaweya Awadalla et al.•ARTICLE•Frontiers in Public Health•2026

    Influenza A outbreaks in Saudi Arabia exhibit different seasonal patterns, influenced by significant changes, including a near-total halt during the COVID-19 pandemic (2020-2021) and a substantial rebound, as evidenced by national surveillance data, until the end of 2023. Traditional time-series models rely on stationarity and stable seasonal patterns; however, these assumptions are significantly undermined by regime shifts. This study introduces…

  • Factors influencing human papillomavirus vaccine uptake among parents and teachers of schoolgirls in Saudi Arabia

    Open Access•Deema Fallatah, Deema I Fallatah et al.•ARTICLE•Frontiers in Public Health•2024

    Introduction: Cervical cancer is a highly prevalent disease among women worldwide. However, the advent of a vaccine against HPV, the main cause of the disease, has prevented its spread. The acceptability of the HPV vaccine to different sectors of the Saudi community has yet to be clarified. Since parents and teachers are major influencers in the decision-making process of vaccination for HPV, this study aimed to assess the knowledge and attitudes…

Sem obras proeminentes nesta página.

  • Factors influencing human papillomavirus vaccine uptake among parents and teachers of schoolgirls in Saudi Arabia

    Open Access•Deema Fallatah, Deema I Fallatah et al.•ARTICLE•Frontiers in Public Health•2024

    Introduction: Cervical cancer is a highly prevalent disease among women worldwide. However, the advent of a vaccine against HPV, the main cause of the disease, has prevented its spread. The acceptability of the HPV vaccine to different sectors of the Saudi community has yet to be clarified. Since parents and teachers are major influencers in the decision-making process of vaccination for HPV, this study aimed to assess the knowledge and attitudes…

  • Early-warning prediction of visceral leishmaniasis mortality using a multivariate STL–deep learning hybrid approach on 20 years of monthly time series

    Open Access•Fathelrhman EL Guma, Maaweya Awadalla et al.•ARTICLE•Frontiers in Public Health•2026

    Introduction Visceral leishmaniasis (VL) is a preventable disease, but continues to cause mortality in Sudan, with transmission dynamics and potentially fatal outcomes strongly affected by local environmental conditions. Methods This research presents an innovative hybrid forecasting framework that amalgamates Seasonal-Trend decomposition using Loess (STL) with four sophisticated models: Gaussian Process Regression (GPR), Long Short-Term Memory (…

  • A hybrid STL–LightGBM framework with probabilistic forecasting for Influenza A incidence in the post-pandemic Saudi Arabia

    Open Access•Reham M Alahmadi, Maaweya Awadalla et al.•ARTICLE•Frontiers in Public Health•2026

    Influenza A outbreaks in Saudi Arabia exhibit different seasonal patterns, influenced by significant changes, including a near-total halt during the COVID-19 pandemic (2020-2021) and a substantial rebound, as evidenced by national surveillance data, until the end of 2023. Traditional time-series models rely on stationarity and stable seasonal patterns; however, these assumptions are significantly undermined by regime shifts. This study introduces…

Cervical Cancer and HPV Research (1 obras) · COVID-19 epidemiological studies (1 obras) · Cross-sectional study (1 obras) · Data-Driven Disease Surveillance (1 obras) · Demography (1 obras) · Environmental health (1 obras) · Family medicine (1 obras) · Field-Flow Fractionation Techniques (1 obras) · Gradient boosting (1 obras) · Health Education and Validation (1 obras)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae