The performance of control charts for large non-normally distributed datasets. - Leo C. E. Huberts; Marit Schoonhoven; Rob Goedhart; Mandla D. Diko; Ronald J. M. M. Does (Qual. Reliab. Eng. Int., 2018)

On the design of control charts with guaranteed conditional performance under estimated parameters. - Ronald J. M. M. Does; Rob Goedhart; William H. Woodall (Qual. Reliab. Eng. Int., 2020)

Processing new types of quality data. - Ronald J. M. M. Does; Rob Goedhart; William H. Woodall (Qual. Reliab. Eng. Int., 2020)

Improved control chart performance using cautious parameter learning. - Leo C. E. Huberts; Rob Goedhart; Ronald J. M. M. Does (Comput. Ind. Eng., 2022)

Why we do need Explainable AI for Healthcare. - Giovanni Cinà; Tabea Röber; Rob Goedhart; S. Ilker Birbil (CoRR, 2022)

Semantic match: Debugging feature attribution methods in XAI for healthcare. - Giovanni Cinà; Tabea E. Röber; Rob Goedhart; S. Ilker Birbil (CHIL, 2023)

Fixing confirmation bias in feature attribution methods via semantic match. - Giovanni Cinà; Daniel Fernandez-Llaneza; Nishant Mishra; Tabea E. Röber; Sandro Pezzelle; Iacer Calixto; Rob Goedhart; S. Ilker Birbil (CoRR, 2023)

Monitoring high-dimensional heteroscedastic processes using rank-based EWMA methods. - Zezhong Wang; Rob Goedhart; Inez Maria Zwetsloot (Comput. Ind. Eng., 2023)

Clinicians' Voice: Fundamental Considerations for XAI in Healthcare. - Tabea Röber; Rob Goedhart; S. Ilker Birbil (CoRR, 2024)

Finding Regions of Counterfactual Explanations via Robust Optimization. - Donato Maragno; Jannis Kurtz; Tabea E. Röber; Rob Goedhart; S. Ilker Birbil; Dick den Hertog (INFORMS J. Comput., 2024)

Comparison of threshold tuning methods for predictive monitoring. - Paulina von Stackelberg; Rob Goedhart; S. Ilker Birbil; Ronald J. M. M. Does (Qual. Reliab. Eng. Int., 2024)