Human-centric responsible NLP methods for Dutch healthcare

Unstructured data is guesstimated to account for 80% of all patient data. Nonetheless, unstructured data is currently severely underused in healthcare because it is noisy, hard to interpret, and privacy-sensitive. In this project, we develop human-centric responsible Natural Language Processing (NLP) and Machine Learning (ML) methods that will allow clinicians and patients to safely tap this unstructured data’s potential. Our proposed methods have a focus on the Dutch healthcare ecosystem and are tailored to support research, education, and patient care by promoting explainable prediction models, ensuring fairness and patient privacy, preventing bias, and coping with data scarcity.

Unstructured data, like free text, is guesstimated to account for 80% of all patient data but is severely underused. This project applies natural language processing and machine learning methods responsibly and reliably to use unstructured data to support research, education, and patient care with focus on the Dutch healthcare ecosystem.