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Andrius Vabalas

Datos Biográficos

ID5082407
NOMBREAndrius Vabalas
NOMBRESAndrius
APELLIDOVabalas
FIRMAVABALAS A
AFILIACIONESUniversity of Helsinki
ORCID0000-0002-0659-2890
VERIFICADOSí
TOTAL DE OBRAS2
TOTAL DE CITAS1
TOTAL COMO AUTOR2
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2019
AÑO MÁS RECIENTE DE PUBLICACIÓN2023
ÍNDICE H1
  • Nationwide health, socio-economic and genetic predictors of Covid-19 vaccination status in Finland

    Open Access•Tuomo Hartonen, Bradley Jermy et al.•ARTICLE•Nature Human Behaviour•2023•Citada por: 1•Referencias: 44

    Understanding factors associated with COVID-19 vaccination can highlight issues in public health systems. Using machine learning, we considered the effects of 2,890 health, socio-economic and demographic factors in the entire Finnish population aged 30–80 and genome-wide information from 273,765 individuals. The strongest predictors of vaccination status were labour income and medication purchase history. Mental health conditions and having unvac…

  • Machine learning algorithm validation with a limited sample size

    Open Access•Andrius Vabalas, Emma Gowen et al.•ARTICLE•PLoS ONE•2019

    Advances in neuroimaging, genomic, motion tracking, eye-tracking and many other technology-based data collection methods have led to a torrent of high dimensional datasets, which commonly have a small number of samples because of the intrinsic high cost of data collection involving human participants. High dimensional data with a small number of samples is of critical importance for identifying biomarkers and conducting feasibility and pilot work…

  • Nationwide health, socio-economic and genetic predictors of Covid-19 vaccination status in Finland

    Open Access•Tuomo Hartonen, Bradley Jermy et al.•ARTICLE•Nature Human Behaviour•2023•Citada por: 1•Referencias: 44

    Understanding factors associated with COVID-19 vaccination can highlight issues in public health systems. Using machine learning, we considered the effects of 2,890 health, socio-economic and demographic factors in the entire Finnish population aged 30–80 and genome-wide information from 273,765 individuals. The strongest predictors of vaccination status were labour income and medication purchase history. Mental health conditions and having unvac…

  • Machine learning algorithm validation with a limited sample size

    Open Access•Andrius Vabalas, Emma Gowen et al.•ARTICLE•PLoS ONE•2019

    Advances in neuroimaging, genomic, motion tracking, eye-tracking and many other technology-based data collection methods have led to a torrent of high dimensional datasets, which commonly have a small number of samples because of the intrinsic high cost of data collection involving human participants. High dimensional data with a small number of samples is of critical importance for identifying biomarkers and conducting feasibility and pilot work…

  • Nationwide health, socio-economic and genetic predictors of Covid-19 vaccination status in Finland

    Open Access•Tuomo Hartonen, Bradley Jermy et al.•ARTICLE•Nature Human Behaviour•2023•Citada por: 1•Referencias: 44

    Understanding factors associated with COVID-19 vaccination can highlight issues in public health systems. Using machine learning, we considered the effects of 2,890 health, socio-economic and demographic factors in the entire Finnish population aged 30–80 and genome-wide information from 273,765 individuals. The strongest predictors of vaccination status were labour income and medication purchase history. Mental health conditions and having unvac…

2019-20 coronavirus outbreak (1 obras) · Artificial Intelligence (1 obras) · Artificial neural network (1 obras) · Cell Image Analysis Techniques (1 obras) · Computer Science (1 obras) · Cross-validation (1 obras) · Data collection (1 obras) · Data mining (1 obras) · Demography (1 obras) · Disease (1 obras)

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