82 citations · 117 across the 8 of their papers we have counts for
10 papers
Surveying (Dis)Parities and Concerns of Compute Hungry NLP Research
Ji-Ung Lee, Haritz Puerto, Betty van Aken +8
Many recent improvements in NLP stem from the development and use of large pre-trained language models (PLMs) with billions of parameters. Large model sizes makes computational cos…
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…
Efficient Methods for Natural Language Processing: A Survey
Marcos Treviso, Ji-Ung Lee, Tianchu Ji +19
Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance mea…
Cross-Lingual Knowledge Transfer for Clinical Phenotyping
Jens-Michalis Papaioannou, Paul Grundmann, Betty van Aken +5
Clinical phenotyping enables the automatic extraction of clinical conditions from patient records, which can be beneficial to doctors and clinics worldwide. However, current state-…
What Do You See in this Patient? Behavioral Testing of Clinical NLP Models
Betty van Aken, Sebastian Herrmann, Alexander Löser
Decision support systems based on clinical notes have the potential to improve patient care by pointing doctors towards overseen risks. Predicting a patient's outcome is an essenti…
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…