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Aniek Markus, MSc PhD Student Email: This email address is being protected from spambots. You need JavaScript enabled to view it. |
Background
Aniek obtained two bachelors in Econometrics and Economics (2017) and a master Business Analytics and Quantitative Marketing (2019) from Erasmus University Rotterdam. She wrote her master thesis on the causal effects of binary, continuous and multivariate treatments using propensity score methods. She worked as a research assistant at the Erasmus School of Health Policy and Management, where she investigated ethnic inequalities in deceased donor kidney allocation and the productivity of Dutch hospitals. Currently, she is pursuing a PhD at the department of Medical Informatics with a focus on explainable artificial intelligence.
Publications
Markus, A. F., Rijnbeek, P. R., & Reps. J. M. (2022). Why predicting risk can’t identify ‘risk factors’: empirical assessment of model stability in machine learning across observational health databases. In Machine Learning for Healthcare 2022 (pp.1-25). PMLR. (links to full text and video).
Markus, A. F., Verhamme, K. M., Kors, J. A., & Rijnbeek, P. R. (2022). TreatmentPatterns: An R package to facilitate the standardized development and analysis of treatment patterns across disease domains. Computer Methods and Programs in Biomedicine, 107081. https://doi.org/10.1016/j.cmpb.2022.107081
Dohmen, P., van Ineveld, M., Markus, A., van der Hagen, L., & van de Klundert, J. (2022). Does competition improve hospital performance: a DEA based evaluation from the Netherlands. The European Journal of Health Economics, 1-19. https://doi.org/10.1007/s10198-022-01529-8
Markus, A. F., Kors, J. A., & Rijnbeek, P. R. (2021). The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies. Journal of Biomedical Informatics, 113, 103655. https://doi.org/10.1016/j.jbi.2020.103655
Van de Klundert, J., van der Hagen, L., & Markus, A. (2021). Eliminating Transplant Waiting Time Inequities-with an application to Kidney Allocation in the USA. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2021.09.033
Markus, A. F., Williams, R. D., Yang, C., Duarte Salles, T., Falconer, T., Jonnagaddala, J., . . . Rijnbeek, P. R. (2020). Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network. BMC Medical Research Methodology, 22(1), 35. https://doi.org/10.1186/s12874-022-01505-z
Presentations
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Machine Learning for Healthcare 2022 & OHDSI Europe Symposium 2022: Why predicting risk can’t identify ‘risk factors’: empirical assessment of model stability in machine learning across observational health databases
Authors: Aniek Markus, Peter Rijnbeek, Jenna Reps
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BeRS-GSK Clinical Science Awards in Pulmonology: real-world treatment patterns of newly diagnosed asthma patients
Authors: Aniek Markus, Peter Rijnbeek, Jan Kors, Guy Brusselle, Katia Verhamme
Poster presentations
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Explaining patient-level prediction models using permutation feature importance and SHAP (OHDSI 2022 Global Symposium)
Authors: Aniek F. Markus, Egill A. Fridgeirsson, Jan A. Kors, Katia M.C. Verhamme, Peter R. Rijnbeek
https://www.ohdsi.org/2022showcase-74/
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Treatment Patterns: An R package to analyze treatment patterns of a study population of interest (OHDSI 2021 Global Symposium)
Authors: Aniek F. Markus, Peter R. Rijnbeek, Jan A. Kors, Katia Verhamme
https://www.ohdsi.org/2021-global-symposium-showcase-70/
- Learning under constraints with EXPLORE (OHDSI 2021 Global Symposium)
Authors: Aniek F. Markus, Jan A. Kors, Peter R. Rijnbeek
https://www.ohdsi.org/2021-global-symposium-showcase-49/
- Real-world treatment patterns of newly diagnosed patients with asthma and/or COPD (ERS International Congress 2021, ICPE 2021)
Authors: Aniek Markus, Peter Rijnbeek, Jan Kors, Guy Brusselle, Ed Burn, Daniel Prieto-Alhambra, Katia Verhamme
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Real-world treatment patterns of newly diagnosed asthma patients (OHDSI 2020 Global Symposium)
Authors: Aniek Markus, Peter Rijnbeek, Jan Kors, Guy Brusselle, Katia Verhamme