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Aniek F. Markus
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Journal Articles
- 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) - 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)
Conference and Workshop Papers
- 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
- [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
Informal and Other Publications
- 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)
Coauthor Index
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