GERNERMED: An open German medical NER model

Recent advancements in natural language processing (NLP) have been achieved by the use of increasingly complex neural networks. In clinical context, NLP is a key technique to access highly relevant information from unstructured texts such as clinical notes. We evaluate the feasibility of training our neural model GERNERMED on annotated German training data generated by automated translation from a public English dataset. The work guides other researchers about the use of machine-translation methods for dataset acquisition. Due to the public origin of the dataset, our trained software can be used by fellow researchers without any legal access restrictions.