Aniek F. Markus - researchr alias

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Viewing Publication 1 - 7 from 7

2023

Semantic Meaningfulness: Evaluating Counterfactual Approaches for Real-World Plausibility and FeasibilityJacqueline Höllig, Aniek F. Markus, Jef de Slegte, Prachi Bagave. xai 2023: 636-659 [doi]

Challenges of Estimating Global Feature Importance in Real-World Health Care DataAniek F. Markus, Egill A. Fridgeirsson, Jan A. Kors, Katia M. C. Verhamme, Peter R. Rijnbeek. mie 2023: 1057-1061 [doi]

2022

TreatmentPatterns: An R package to facilitate the standardized development and analysis of treatment patterns across disease domainsAniek F. Markus, Katia M. C. Verhamme, Jan A. Kors, Peter R. Rijnbeek. cmpb, 225:107081, 2022. [doi]

Why predicting risk can't identify 'risk factors': empirical assessment of model stability in machine learning across observational health databasesAniek F. Markus, Peter R. Rijnbeek, Jenna Marie Reps. mlhc 2022: 828-852 [doi]

Use of unstructured text in prognostic clinical prediction models: a systematic reviewTom 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. jamia, 29(7):1292-1302, 2022. [doi]

Trends in the conduct and reporting of clinical prediction model development and validation: a systematic reviewCynthia 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. jamia, 29(5):983-989, 2022. [doi]

2021

The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategiesAniek F. Markus, Jan A. Kors, Peter R. Rijnbeek. jbi, 113:103655, 2021. [doi]

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