Michaela Kaleta was a data research assistant at the CSH Vienna until June 2022. She obtained her bachelor’s and master’s degree in physics from the University of Vienna in 2016 and 2019, respectively.
For her master’s thesis (“Modelling path-dependent diffusion processes on complex healthcare networks”), Michaela joined Peter Klimek’s research group for medical data analysis at the Complexity Science Hub Vienna and Medical University of Vienna. The group is interested in how patients’ steps through the healthcare system can be modelled using analogies to simple diffusion processes like the Markov process. In cooperation with medical experts the group also revealed the risk-reducing effects of doctoral visits on patients’ re-hospitalization probability.
Currently, Michaela continues her analysis of medical claims datasets with focus on type 2 diabetes patients in Austria. In particular, she is interested in regional variabilities of diabetes prevalence and the possible severe complications that may result from this widespread disease.
M. Kaleta, J. Lasser, E. Dervic, et al.
Stress-testing the resilience of the Austrian healthcare system using agent-based simulation
Nature Communications 13 (4259) (2022)
K. Ledebur, M. Kaleta, et al.
Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria
PLoS Comput Biol 18(4) (2022) e1009973
M. Leutner, et al.
Major Depressive Disorder (MDD) and antidepressant medication are overrepresented in high-dose Statin treatment
Frontiers in Medicine 8 (2021) 608083
M. Kaleta, [...] P. Klimek et al.
How specialist aftercare impacts long-term readmission risks in elderly patients with metabolic, cardiac, and chronic obstructive pulmonary diseases (…)
JMIR Med Inform 8 (9) (2020) e18147