12 citations · 22 across the 4 of their papers we have counts for
6 papers
This Patient Looks Like That Patient: Prototypical Networks for Interpretable Diagnosis Prediction from Clinical Text
Betty van Aken, Jens-Michalis Papaioannou, Marcel G. Naik +4
The use of deep neural models for diagnosis prediction from clinical text has shown promising results. However, in clinical practice such models must not only be accurate, but prov…
Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integration
Betty van Aken, Jens-Michalis Papaioannou, Manuel Mayrdorfer +3
Outcome prediction from clinical text can prevent doctors from overlooking possible risks and help hospitals to plan capacities. We simulate patients at admission time, when decisi…
VisBERT: Hidden-State Visualizations for Transformers
Betty van Aken, Benjamin Winter, Alexander Löser +1
Explainability and interpretability are two important concepts, the absence of which can and should impede the application of well-performing neural networks to real-world problems…
Learning Contextualized Document Representations for Healthcare Answer Retrieval
Sebastian Arnold, Betty van Aken, Paul Grundmann +2
We present Contextual Discourse Vectors (CDV), a distributed document representation for efficient answer retrieval from long healthcare documents. Our approach is based on structu…
How Does BERT Answer Questions? A Layer-Wise Analysis of Transformer Representations
Betty van Aken, Benjamin Winter, Alexander Löser +1
Bidirectional Encoder Representations from Transformers (BERT) reach state-of-the-art results in a variety of Natural Language Processing tasks. However, understanding of their int…
Challenges for Toxic Comment Classification: An In-Depth Error Analysis
Betty van Aken, Julian Risch, Ralf Krestel +1
Toxic comment classification has become an active research field with many recently proposed approaches. However, while these approaches address some of the task's challenges other…