| Deep learning approaches outperform conventional strategies in de-identification of German medical reports P Richter-Pechanski, A Amr, HA Katus, C Dieterich German Medical Data Sciences: Shaping Change–Creative Solutions for …, 2019 | 29 | 2019 |
| De-identification of German medical admission notes P Richter-Pechanski, S Riezler, C Dieterich German Medical Data Sciences: A Learning Healthcare System, 165-169, 2018 | 27 | 2018 |
| Automatic extraction of 12 cardiovascular concepts from German discharge letters using pre-trained language models P Richter-Pechanski, NA Geis, C Kiriakou, DM Schwab, C Dieterich Digital health 7, 20552076211057662, 2021 | 14 | 2021 |
| A distributable German clinical corpus containing cardiovascular clinical routine doctor’s letters P Richter-Pechanski, P Wiesenbach, DM Schwab, C Kiriakou, M He, ... Scientific Data 10 (1), 207, 2023 | 11 | 2023 |
| Preliminary analysis of structured reporting in the HiGHmed use case cardiology: challenges and measures A Kindermann, E Tute, S Benda, M Löpprich, P Richter-Pechanski, ... German Medical Data Sciences: Bringing Data to Life, 187-194, 2021 | 8 | 2021 |
| Clinical information extraction for lower-resource languages and domains with few-shot learning using pretrained language models and prompting P Richter-Pechanski, P Wiesenbach, DM Schwab, C Kiriakou, N Geis, ... Natural Language Processing, 1-24, 2024 | 3 | 2024 |
| Few-Shot and Prompt Training for Text Classification in German Doctor’s Letters P Richter-Pechanski, P Wiesenbach, DM Schwab, C Kiriakou, M He, ... Caring is Sharing–Exploiting the Value in Data for Health and Innovation …, 2023 | 2 | 2023 |
