Meine Artikel finden Sie auch auf meinem Google Scholar Profil.
Published in Sammelband (Book Chapter), 2025
A book chapter on transfer learning methods for the classification of medical texts, building on ontology-based approaches to enable GDPR-compliant model reuse across institutions.
Recommended citation: Bruneß, D. et al. (2025). Transfer-Lernen für die Klassifikation medizinischer Texte.
Published in Healthcare Transformation with Informatics and Artificial Intelligence (IOS Press), 2023
A transfer learning method that uses ontologies to normalize the feature space of text classifiers to create a controlled vocabulary that ensures that the trained models do not contain personal data, and can be widely reused without violating the GDPR.
Recommended citation: Bruneß, D., Bay, M., Schulze, C., Guckert, M., & Minor, M. (2023). A Hybrid AI-Based Method for ICD Classification of Medical Documents. Healthcare Transformation with Informatics and Artificial Intelligence, 305, 1-4.. https://doi.org/10.3233/SHTI230408
Published in 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 2022
A transfer learning method which uses ontologies to normalise the feature space of text classifiers to guarantee that the trained models do not contain any person related data and can therefore be widely reused without raising General Data Protection Regulation issues.
Recommended citation: Bruneß, D., Bay, M., Schulze, C., Guckert, M., & Minor, M. (2022). An Ontology-based transfer learning method improving classification of medical documents. 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 407-412. https://doi.org/10.1109/ICMLA55696.2022.00065
Published in 2020 6th IEEE Congress on Information Science and Technology (CiSt), 2021
A new method for the extraction of discipline-specific terms from medical documents using word embeddings in a neighborhood context based method which is called Snowball because of its layerwise way of working.
Recommended citation: Bay, M., Bruneß, D., Herold, M., Schulze, C., Guckert, M., & Minor, M. (2020). Term Extraction from Medical Documents Using Word Embeddings. 2020 6th IEEE Congress on Information Science and Technology (CiSt), 328-333. https://doi.org/10.1109/CiSt49399.2021.9357263
Published in The Art of Theoretical Biology, 2020
The bacterial pathogen Salmonella Typhimurium provokes gastroenteritis and typhoid fever. Salmonella become multidrug resistant.
Recommended citation: Rieser, J., Bruneß, D., Ackermann, J., Koch, I. (2020). Interacting Spider Webs. In: Matthäus, F., Matthäus, S., Harris, S., Hillen, T. (eds) The Art of Theoretical Biology. Springer https://doi.org/10.1007/978-3-030-33471-0_68
Published in Bioinformatics, 2016
A new, extended version of the Protein Topology Graph Library web server is presented, featuring additional information on ligand binding to secondary structure elements, increased usability and an application programming interface (API) to retrieve data, allowing for an automated analysis of protein topology.
Recommended citation: Schäfer, T., Scheck, A., Bruneß, D., May, P., & Koch, I. (2016). The new protein topology graph library web server. Bioinformatics, 32 3, 474-6 . https://doi.org/10.1093/bioinformatics%2Fbtv574