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ORCIDAniek F. Markus
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2020 – today
- 2023
[c3]Aniek F. Markus, Egill A. Fridgeirsson, Jan A. Kors, Katia M. C. Verhamme, Peter R. Rijnbeek:
Challenges of Estimating Global Feature Importance in Real-World Health Care Data. MIE 2023: 1057-1061- [c2]Jacqueline Höllig
, Aniek F. Markus, Jef de Slegte, Prachi Bagave:
Semantic Meaningfulness: Evaluating Counterfactual Approaches for Real-World Plausibility and Feasibility. xAI (2) 2023: 636-659 - 2022
- [j5]Aniek F. Markus, Katia M. C. Verhamme, Jan A. Kors, Peter R. Rijnbeek:
TreatmentPatterns: An R package to facilitate the standardized development and analysis of treatment patterns across disease domains. Comput. Methods Programs Biomed. 225: 107081 (2022) - [j4]Joris van de Klundert, Liana van der Hagen, Aniek F. Markus:
Eliminating transplant waiting time inequities - With an application to kidney allocation in the USA. Eur. J. Oper. Res. 297(3): 977-985 (2022) - [j3]Cynthia Yang, Jan A. Kors, Solomon Ioannou, Luis H. John, Aniek F. Markus, Alexandros Rekkas, Maria A. J. de Ridder, Tom M. Seinen, Ross D. Williams, Peter R. Rijnbeek:
Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review. J. Am. Medical Informatics Assoc. 29(5): 983-989 (2022) - [j2]Tom M. Seinen, Egill A. Fridgeirsson, Solomon Ioannou, Daniel Jeannetot, Luis H. John, Jan A. Kors, Aniek F. Markus, Victor Pera, Alexandros Rekkas, Ross D. Williams, Cynthia Yang, Erik M. van Mulligen, Peter R. Rijnbeek:
Use of unstructured text in prognostic clinical prediction models: a systematic review. J. Am. Medical Informatics Assoc. 29(7): 1292-1302 (2022) - [c1]Aniek F. Markus, Peter R. Rijnbeek, Jenna Marie Reps:
Why predicting risk can't identify 'risk factors': empirical assessment of model stability in machine learning across observational health databases. MLHC 2022: 828-852 - 2021
- [j1]Aniek F. Markus, Jan A. Kors, Peter R. Rijnbeek:
The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies. J. Biomed. Informatics 113: 103655 (2021) - 2020
- [i1]Aniek F. Markus, Jan A. Kors, Peter R. Rijnbeek:
The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategies. CoRR abs/2007.15911 (2020)
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