Time-to-Birth Prediction Models and the Influence of Expert Opinions. - Gilles Vandewiele; Isabelle Dehaene; Olivier Janssens; Femke Ongenae; Femke De Backere; Filip De Turck; Kristien Roelens; Sofie Van Hoecke; Thomas Demeester (AIME, 2019)

A Critical Look at Studies Applying Over-Sampling on the TPEHGDB Dataset. - Gilles Vandewiele; Isabelle Dehaene; Olivier Janssens; Femke Ongenae; Femke De Backere; Filip De Turck; Kristien Roelens; Sofie Van Hoecke; Thomas Demeester (AIME, 2019)

Overly Optimistic Prediction Results on Imbalanced Data: Flaws and Benefits of Applying Over-sampling. - Gilles Vandewiele; Isabelle Dehaene; György Kovács 002; Lucas Sterckx; Olivier Janssens; Femke Ongenae; Femke De Backere; Filip De Turck; Kristien Roelens; Johan Decruyenaere; Sofie Van Hoecke; Thomas Demeester (CoRR, 2020)

Clinical information extraction for preterm birth risk prediction. - Lucas Sterckx; Gilles Vandewiele; Isabelle Dehaene; Olivier Janssens; Femke Ongenae; Femke De Backere; Filip De Turck; Kristien Roelens; Johan Decruyenaere; Sofie Van Hoecke; Thomas Demeester (J. Biomed. Informatics, 2020)

Overly optimistic prediction results on imbalanced data: a case study of flaws and benefits when applying over-sampling. - Gilles Vandewiele; Isabelle Dehaene; György Kovács 002; Lucas Sterckx; Olivier Janssens; Femke Ongenae; Femke De Backere; Filip De Turck; Kristien Roelens; Johan Decruyenaere; Sofie Van Hoecke; Thomas Demeester (Artif. Intell. Medicine, 2021)

Generalizability of AI Survival Models in the Context of Preterm Birth Prediction. - Anne M. Fischer; Isabelle Dehaene; Mark Hoogendoorn (AIME (2), 2025)