Publikation
Proposal of Semantic Annotation for German Metadata Using Bidirectional Recurrent Neural Networks
Hannes Ulrich; Hristina Uzunova; Heinz Handels; Josef Ingenerf
In: Studies in Health Technology and Informatics, Vol. 294, Pages 357-361, IOS Press, 2022.
Zusammenfassung
The distributed nature of our digital healthcare and the rapid emergence
of new data sources prevents a compelling overview and the joint use of new data.
Data integration, e.g., with metadata and semantic annotations, is expected to
overcome this challenge. In this paper, we present an approach to predict UMLS
codes to given German metadata using recurrent neural networks. The augmentation
of the training dataset using the Medical Subject Headings (MeSH), particularly the
German translations, also improved the model accuracy. The model demonstrates
robust performance with 75% accuracy and aims to show that increasingly
sophisticated machine learning tools can already play a significant role in data
integration.