Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Matjaž Gams

Biographic Data

ID5054463
NAMEMatjaž Gams
GIVEN NAMESMatjaž
FAMILY NAMEGams
SIGNATUREGAMS M
AFFILIATIONSJožef Stefan Institute
ORCID0000-0002-5747-0711
VERIFIEDYes
TOTAL WORKS5
TOTAL CITATIONS1
WORKS AS AUTHOR5
WORKS AS EDITOR0
FIRST PUBLICATION YEAR1998
LATEST PUBLICATION YEAR2023
H-INDEX1
  • 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 …

  • Persuasive Technology for Mental Health

    Open Access•Tine Kolenik, Matjaž Gams•ARTICLE•IEEE Technology and Society…•2021

    The increasing trend of mental health issues, especially among younger people, is not a new phenomenon. World organizations, leaders, and decision-makers are recognizing its devastating effect, resulting in mental health well-being appearing in goal 3 of the 17 UN sustainable development goals (SDGs) [1] . Among mental health issues, stress, anxiety, and depression (SAD) seem to be on the forefront—reaching 74% for disabling stress [2] , 28% for …

  • Machine Learning for Analyzing Non-Countermeasure Factors Affecting Early Spread of Covid-19

    Open Access•Vito Janko, Gašper Slapničar et al.•ARTICLE•International Journal of…•2021

    The COVID-19 pandemic affected the whole world, but not all countries were impacted equally. This opens the question of what factors can explain the initial faster spread in some countries compared to others. Many such factors are overshadowed by the effect of the countermeasures, so we studied the early phases of the infection when countermeasures had not yet taken place. We collected the most diverse dataset of potentially relevant factors and …

  • CulturalErica

    Open Access•Octavian-Mihai Machidon, Octavian Machidon et al.•ARTICLE•Journal of Cultural Heritage•2020•Cited by: 1•References: 15

  • Improvements in slovene text-to-speech synthesis

    Tomaz Sef, Ales Dobnikar et al.•CONFERENCE•5th International Conference on…•1998

  • CulturalErica

    Open Access•Octavian-Mihai Machidon, Octavian Machidon et al.•ARTICLE•Journal of Cultural Heritage•2020•Cited by: 1•References: 15

  • Improvements in slovene text-to-speech synthesis

    Tomaz Sef, Ales Dobnikar et al.•CONFERENCE•5th International Conference on…•1998

  • CulturalErica

    Open Access•Octavian-Mihai Machidon, Octavian Machidon et al.•ARTICLE•Journal of Cultural Heritage•2020•Cited by: 1•References: 15

  • Persuasive Technology for Mental Health

    Open Access•Tine Kolenik, Matjaž Gams•ARTICLE•IEEE Technology and Society…•2021

    The increasing trend of mental health issues, especially among younger people, is not a new phenomenon. World organizations, leaders, and decision-makers are recognizing its devastating effect, resulting in mental health well-being appearing in goal 3 of the 17 UN sustainable development goals (SDGs) [1] . Among mental health issues, stress, anxiety, and depression (SAD) seem to be on the forefront—reaching 74% for disabling stress [2] , 28% for …

  • Machine Learning for Analyzing Non-Countermeasure Factors Affecting Early Spread of Covid-19

    Open Access•Vito Janko, Gašper Slapničar et al.•ARTICLE•International Journal of…•2021

    The COVID-19 pandemic affected the whole world, but not all countries were impacted equally. This opens the question of what factors can explain the initial faster spread in some countries compared to others. Many such factors are overshadowed by the effect of the countermeasures, so we studied the early phases of the infection when countermeasures had not yet taken place. We collected the most diverse dataset of potentially relevant factors and …

  • 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 …

Computer Science (5 works) · Artificial Intelligence (2 works) · COVID-19 epidemiological studies (2 works) · COVID-19 Pandemic Impacts (2 works) · Economics (2 works) · Machine learning (2 works) · Medicine (2 works) · Pandemic (2 works) · Psychology (2 works) · Algorithm (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