Betty Van Aken

Betty Van Aken is a researcher specializing in Natural Language Processing with significant contributions to Clinical NLP and Efficient Methods. Her work focuses on interpretable AI, cross-lingual knowledge transfer, and behavioral testing of clinical models, as evidenced by publications in top venues like ACL, EACL, and ClinicalNLP.

Her research interests span:

• Interpretable AI for clinical decision support
• Efficient NLP methods under resource constraints
• Cross-lingual transfer learning in medical domains
• Outcome prediction from clinical text
• Assertion detection in patient records
• Toxic comment classification and error analysis

Betty's publications from 2018-2023 demonstrate expertise in model design, dataset annotation, and addressing systemic biases. She collaborates extensively with experts in computational linguistics and medical informatics, including Alexander Löser and Felix Gers.