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Saeed Shakibfar

Datos Biográficos

ID10019481
NOMBRESaeed Shakibfar
NOMBRESSaeed
APELLIDOShakibfar
FIRMASHAKIBFAR S
AFILIACIONESUniversity of Copenhagen
ORCID0000-0001-8399-0318
VERIFICADOSí
TOTAL DE OBRAS2
TOTAL DE CITAS0
TOTAL COMO AUTOR2
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2023
AÑO MÁS RECIENTE DE PUBLICACIÓN2023
ÍNDICE H0
  • Artificial intelligence-driven prediction of Covid-19-related hospitalization and death

    Open Access•Saeed Shakibfar, Fredrik Nyberg et al.•ARTICLE•Frontiers in Public Health•2023

  • Machine learning-driven development of a disease risk score for Covid-19 hospitalization and mortality

    Open Access•Saeed Shakibfar, Jing Zhao et al.•ARTICLE•Frontiers in Public Health•2023

    Aims: To develop a disease risk score for COVID-19-related hospitalization and mortality in Sweden and externally validate it in Norway. Method: We employed linked data from the national health registries of Sweden and Norway to conduct our study. We focused on individuals in Sweden with confirmed SARS-CoV-2 infection through RT-PCR testing up to August 2022 as our study cohort. Within this group, we identified hospitalized cases as those who wer…

Sin obras prominentes en esta página.

  • Artificial intelligence-driven prediction of Covid-19-related hospitalization and death

    Open Access•Saeed Shakibfar, Fredrik Nyberg et al.•ARTICLE•Frontiers in Public Health•2023

  • Machine learning-driven development of a disease risk score for Covid-19 hospitalization and mortality

    Open Access•Saeed Shakibfar, Jing Zhao et al.•ARTICLE•Frontiers in Public Health•2023

    Aims: To develop a disease risk score for COVID-19-related hospitalization and mortality in Sweden and externally validate it in Norway. Method: We employed linked data from the national health registries of Sweden and Norway to conduct our study. We focused on individuals in Sweden with confirmed SARS-CoV-2 infection through RT-PCR testing up to August 2022 as our study cohort. Within this group, we identified hospitalized cases as those who wer…

2019-20 coronavirus outbreak (1 obras) · Computer Science (1 obras) · COVID-19 and healthcare impacts (1 obras) · COVID-19 Clinical Research Studies (1 obras) · Disease (1 obras) · Internal Medicine (1 obras) · Long-Term Effects of COVID-19 (1 obras) · Medicine (1 obras) · Norwegian (1 obras) · Outbreak (1 obras)

Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae