1 citations · 1 across the 3 of their papers we have counts for
5 papers
Dynamic Expert-Guided Model Averaging for Causal Discovery
Adrick Tench, Thomas Demeester
Would-be practitioners of causal discovery face a dizzying array of algorithms without a clear best choice. This abundance of competitive methods makes ensembling a natural strateg…
Patient-level Information Extraction by Consistent Integration of Textual and Tabular Evidence with Bayesian Networks
Paloma Rabaey, Adrick Tench, Stefan Heytens +1
Electronic health records (EHRs) form an invaluable resource for training clinical decision support systems. To leverage the potential of such systems in high-risk applications, we…
Modeling Clinical Uncertainty in Radiology Reports: from Explicit Uncertainty Markers to Implicit Reasoning Pathways
Paloma Rabaey, Jong Hak Moon, Jung-Oh Lee +4
Radiology reports are invaluable for clinical decision-making and hold great potential for automated analysis when structured into machine-readable formats. These reports often con…
Prior Knowledge Injection into Deep Learning Models Predicting Gene Expression from Whole Slide Images
Max Hallemeesch, Marija Pizurica, Paloma Rabaey +3
Cancer diagnosis and prognosis primarily depend on clinical parameters such as age and tumor grade, and are increasingly complemented by molecular data, such as gene expression, fr…
Debiasing Synthetic Data Generated by Deep Generative Models
Alexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey +4
While synthetic data hold great promise for privacy protection, their statistical analysis poses significant challenges that necessitate innovative solutions. The use of deep gener…