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Tea Tušar

Biographic Data

ID9211695
NAMETea Tušar
GIVEN NAMESTea
FAMILY NAMETušar
SIGNATURETUŠAR T
AFFILIATIONSJožef Stefan Institute
ORCID0000-0002-6495-006X
VERIFIEDYes
TOTAL WORKS1
TOTAL CITATIONS0
WORKS AS AUTHOR1
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2023
LATEST PUBLICATION YEAR2023
H-INDEX0
  • Optimizing non-pharmaceutical intervention strategies against Covid-19 using artificial intelligence

    Open Access•Vito Janko, Nina Reščič et al.•ARTICLE•Frontiers in Public Health•2023

    One key task in the early fight against the COVID-19 pandemic was to plan non-pharmaceutical interventions to reduce the spread of the infection while limiting the burden on the society and economy. With more data on the pandemic being generated, it became possible to model both the infection trends and intervention costs, transforming the creation of an intervention plan into a computational optimization problem. This paper proposes a framework …

No prominent works on this page.

  • Optimizing non-pharmaceutical intervention strategies against Covid-19 using artificial intelligence

    Open Access•Vito Janko, Nina Reščič et al.•ARTICLE•Frontiers in Public Health•2023

    One key task in the early fight against the COVID-19 pandemic was to plan non-pharmaceutical interventions to reduce the spread of the infection while limiting the burden on the society and economy. With more data on the pandemic being generated, it became possible to model both the infection trends and intervention costs, transforming the creation of an intervention plan into a computational optimization problem. This paper proposes a framework …

Artificial Intelligence (1 work) · Computer Science (1 work) · COVID-19 epidemiological studies (1 work) · COVID-19 Pandemic Impacts (1 work) · Economics (1 work) · Geography (1 work) · Machine learning (1 work) · Medicine (1 work) · Nursing (1 work) · Pandemic (1 work)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae