5 papers
Rank-Learner: Orthogonal Ranking of Treatment Effects
Henri Arno, Dennis Frauen, Emil Javurek +2
Many decision-making problems require ranking individuals by their treatment effects rather than estimating the exact effect magnitudes. Examples include prioritizing patients for…
Annotation-Assisted Learning of Treatment Policies From Multimodal Electronic Health Records
Henri Arno, Thomas Demeester
We study how to learn treatment policies from multimodal electronic health records (EHRs) that consist of tabular data and clinical text. These policies can help physicians make be…
From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding
Henri Arno, Paloma Rabaey, Thomas Demeester
One of the central goals of causal machine learning is the accurate estimation of heterogeneous treatment effects from observational data. In recent years, meta-learning has emerge…
From Numbers to Words: Multi-Modal Bankruptcy Prediction Using the ECL Dataset
Henri Arno, Klaas Mulier, Joke Baeck +1
In this paper, we present ECL, a novel multi-modal dataset containing the textual and numerical data from corporate 10K filings and associated binary bankruptcy labels. Furthermore…
Next-Year Bankruptcy Prediction from Textual Data: Benchmark and Baselines
Henri Arno, Klaas Mulier, Joke Baeck +1
Models for bankruptcy prediction are useful in several real-world scenarios, and multiple research contributions have been devoted to the task, based on structured (numerical) as w…