Mitja Luštrek
Biographic Data
| ID | 7856951 |
|---|---|
| NAME | Mitja Luštrek |
| GIVEN NAMES | Mitja |
| FAMILY NAME | Luštrek |
| SIGNATURE | LUŠTREK M |
| AFFILIATIONS | Jožef Stefan Institute |
| ORCID | 0000-0003-3219-2935 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Optimizing non-pharmaceutical intervention strategies against Covid-19 using artificial intelligence
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 …
Sources of Occupational Stress among Office Workers—A Focus Group Study
Workplace stress remains a major interest of occupational health research, usually based on theoretical models and quantitative large-scale studies. Office workers are especially exposed to stressors such as high workload and time pressure. The aim of this qualitative research was to follow a phenomenological approach to identify work stressors as they are perceived by office workers. Six focus groups with office workers of different occupations …
Machine Learning for Analyzing Non-Countermeasure Factors Affecting Early Spread of Covid-19
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 …
Protocol of the STRess at Work (STRAW) Project
Several studies have reported on increasing psychosocial stress in academia due to work environment risk factors like job insecurity, work-family conflict, research grant applications, and high workload. The STRAW project adds novel aspects to occupational stress research among academic staff by measuring day-to-day stress in their real-world work environments over 15 working days. Work environment risk factors, stress outcomes, health-related be…
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Protocol of the STRess at Work (STRAW) Project
Several studies have reported on increasing psychosocial stress in academia due to work environment risk factors like job insecurity, work-family conflict, research grant applications, and high workload. The STRAW project adds novel aspects to occupational stress research among academic staff by measuring day-to-day stress in their real-world work environments over 15 working days. Work environment risk factors, stress outcomes, health-related be…
Machine Learning for Analyzing Non-Countermeasure Factors Affecting Early Spread of Covid-19
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 …
Sources of Occupational Stress among Office Workers—A Focus Group Study
Workplace stress remains a major interest of occupational health research, usually based on theoretical models and quantitative large-scale studies. Office workers are especially exposed to stressors such as high workload and time pressure. The aim of this qualitative research was to follow a phenomenological approach to identify work stressors as they are perceived by office workers. Six focus groups with office workers of different occupations …
Optimizing non-pharmaceutical intervention strategies against Covid-19 using artificial intelligence
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 …
Medicine (4 works) · Computer Science (3 works) · Psychology (3 works) · Applied Psychology (2 works) · Applied Psychology (2 works) · Artificial Intelligence (2 works) · COVID-19 epidemiological studies (2 works) · COVID-19 Pandemic Impacts (2 works) · Machine learning (2 works) · Occupational stress (2 works)