Paloma Rabaey

About Me

I am a Ph.D. student at the T2K research group at IDLab Ghent. Currently, my research focuses on finding ways to include expert knowledge in deep learning models. I am especially interested in applying these ideas to practical use-cases in healthcare, to improve trustworthiness and interpretability of clinical decision support systems. My research is funded by FWO Flanders. In my free time I love to crochet, travel, read and go to the cinema, among many other things.

Research Interests

• ML for healthcare: clinical decision support systems, injection of expert knowledge into ML models
• Bayesian networks: integrate text into Bayesian networks, regularize neural networks with knowledge of causal Bayesian network structure
• Causal Machine Learning: causal neural networks, partial causal discovery, causal inference with Bayesian networks
• Natural Language Processing: information extraction from unstructured clinical notes

Talks

• Clinical Reasoning over Tabular Data and Text with Bayesian Networks. Oral presentation at the 2024 Conference of Artificial Intelligence in Medicine (AIME), in Salt Lake City, Utah. [Slides]
• Why we need Neuro-Symbolic Methods for Clinical Information Extraction. Oral presentation at the Workshop “Primary Care: Electronic Scribes and More” at the 2024 Conference of Artificial Intelligence in Medicine (AIME), in Salt Lake City, Utah. [Slides]

Publications

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