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

Counterfactual Explanations Using Optimization With Constraint Learning. - Donato Maragno; Tabea E. Röber; 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)

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)

Rule generation for classification: Scalability, interpretability, and fairness. - Tabea E. Röber; Adia C. Lumadjeng; M. Hakan Akyüz; S. Ilker Birbil (Comput. Oper. Res., 2025)