Aniek F. Markus

According to our database, Aniek F. Markus authored at least 8 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Semantic Meaningfulness: Evaluating Counterfactual Approaches for Real-World Plausibility and Feasibility.

Jacqueline Höllig, Aniek F. Markus, Jef de Slegte, Prachi Bagave

Proceedings of the Explainable Artificial Intelligence, 2023

Challenges of Estimating Global Feature Importance in Real-World Health Care Data.

Aniek F. Markus, Egill A. Fridgeirsson, Jan A. Kors, Katia M. C. Verhamme, Peter R. Rijnbeek

Proceedings of the Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023, Gothenburg, Sweden, 22, 2023

2022

Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review.

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

J. Am. Medical Informatics Assoc., 2022

Use of unstructured text in prognostic clinical prediction models: a systematic review.

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

J. Am. Medical Informatics Assoc., 2022

Eliminating transplant waiting time inequities - With an application to kidney allocation in the USA.

Joris van de Klundert, Liana van der Hagen, Aniek F. Markus

Eur. J. Oper. Res., 2022

TreatmentPatterns: An R package to facilitate the standardized development and analysis of treatment patterns across disease domains.

Aniek F. Markus, Katia M. C. Verhamme, Jan A. Kors, Peter R. Rijnbeek

Comput. Methods Programs Biomed., 2022

Why predicting risk can't identify 'risk factors': empirical assessment of model stability in machine learning across observational health databases.

Aniek F. Markus, Peter R. Rijnbeek, Jenna Marie Reps

Proceedings of the Machine Learning for Healthcare Conference, 2022

2021

The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies.

Aniek F. Markus, Jan A. Kors, Peter R. Rijnbeek

J. Biomed. Informatics, 2021