Aniek F. Markus

Publication Activity (10 Years)

Years Active: 2020-2023
Publications (10 Years): 8

Top Topics

Unstructured Text

Temporal Trends

Systematic Review

Top Venues

J. Am. Medical Informatics Assoc.

Publications

Jacqueline Höllig, Aniek F. Markus, Jef de Slegte, Prachi Bagave
Semantic Meaningfulness: Evaluating Counterfactual Approaches for Real-World Plausibility and Feasibility. xAI (2) (2023)
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)
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) (2022)
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 (2022)
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) (2022)
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)
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 (2021)
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 (2020)