| Opportunities and challenges in machine learning‐based newborn screening—A systematic literature review E Zaunseder, S Haupt, U Mütze, SF Garbade, S Kölker, V Heuveline JIMD reports 63 (3), 250-261, 2022 | 18 | 2022 |
| Machine learning methods improve specificity in newborn screening for isovaleric aciduria E Zaunseder, U Mütze, SF Garbade, S Haupt, P Feyh, GF Hoffmann, ... Metabolites 13 (2), 304, 2023 | 9 | 2023 |
| Air Quality Monitoring and Data Management in Germany-Status Quo and Suggestions for Improvement L Petry, H Herold, G Meinel, T Meiers, I Müller, E Kalusche, T Erbertseder, ... The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2020 | 7 | 2020 |
| High accuracy forecasting with limited input data: Using FFNNs to predict offshore wind power generation E Zaunseder, L Müller, S Blankenburg Proceedings of the 9th International Symposium on Information and …, 2018 | 6 | 2018 |
| Comparing the robustness of classical and deep learning techniques for text classification Q Tran, K Shpileuskaya, E Zaunseder, L Putzar, S Blankenburg 2022 International Joint Conference on Neural Networks (IJCNN), 1-10, 2022 | 5 | 2022 |
| Personalized metabolic whole-body models for newborns and infants predict growth and biomarkers of inherited metabolic diseases E Zaunseder, U Mütze, JG Okun, GF Hoffmann, S Kölker, V Heuveline, ... Cell Metabolism, 2023 | 1 | 2023 |
| Deep Learning and Explainable Artificial Intelligence for Improving Specificity and Detecting Metabolic Patterns in Newborn Screening E Zaunseder, U Mütze, SF Garbade, S Haupt, S Kölker, V Heuveline 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 1566-1571, 2023 | | 2023 |
| Robustness Analysis uncovers Language Proficiency Bias in Emotion Recognition Systems Q Tran, K Shpileuskaya, E Zaunseder, J Salg, L Putzar, S Blankenburg 2023 11th International Conference on Affective Computing and Intelligent …, 2023 | | 2023 |
