| Telemedicine in Germany during the COVID-19 pandemic: multi-professional national survey A Peine, P Paffenholz, L Martin, S Dohmen, G Marx, SH Loosen Journal of medical Internet research 22 (8), e19745, 2020 | 118 | 2020 |
| Self-directed learning can outperform direct instruction in the course of a modern German medical curriculum-results of a mixed methods trial A Peine, K Kabino, C Spreckelsen BMC medical education 16, 1-11, 2016 | 96 | 2016 |
| Perception of the 2020 SARS-CoV-2 pandemic among medical professionals in Germany: results from a nationwide online survey P Paffenholz, A Peine, M Hellmich, SV Paffenholz, L Martin, M Luedde, ... Emerging microbes & infections 9 (1), 1590-1599, 2020 | 67 | 2020 |
| Development and validation of a reinforcement learning algorithm to dynamically optimize mechanical ventilation in critical care A Peine, A Hallawa, J Bickenbach, G Dartmann, LB Fazlic, A Schmeink, ... NPJ digital medicine 4 (1), 32, 2021 | 65 | 2021 |
| Impact of the COVID-19 Pandemic on Urologists in Germany P Paffenholz, A Peine, N Fischer, M Hellmich, D Pfister, A Heidenreich, ... European Urology Focus 6 (5), 1111-1119, 2020 | 40 | 2020 |
| Prediction of prolonged ICU stay in cardiac surgery patients as a useful method to identify nutrition risk in cardiac surgery patients: a post hoc analysis of a prospective … C Stoppe, J Ney, VV Lomivorotov, SM Efremov, C Benstoem, A Hill, ... Journal of Parenteral and Enteral Nutrition 43 (6), 768-779, 2019 | 25 | 2019 |
| An innovative telemedical network to improve infectious disease management in critically ill patients and outpatients (TELnet@ NRW): stepped-wedge cluster randomized controlled … G Marx, W Greiner, C Juhra, S Elkenkamp, D Gensorowsky, S Lemmen, ... Journal of Medical Internet Research 24 (3), e34098, 2022 | 19 | 2022 |
| Evo-RL: evolutionary-driven reinforcement learning A Hallawa, T Born, A Schmeink, G Dartmann, A Peine, L Martin, G Iacca, ... Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021 | 19 | 2021 |
| A novel NLP-fuzzy system prototype for information extraction from medical guidelines LB Fazlic, A Hallawa, A Schmeink, A Peine, L Martin, G Dartmann 2019 42nd International Convention on Information and Communication …, 2019 | 18 | 2019 |
| A deep learning approach for managing medical consumable materials in intensive care units via convolutional neural networks: technical proof-of-concept study A Peine, A Hallawa, O Schöffski, G Dartmann, LB Fazlic, A Schmeink, ... JMIR medical informatics 7 (4), e14806, 2019 | 14 | 2019 |
| Localization-driven speech enhancement in noisy multi-speaker hospital environments using deep learning and meta learning M Barhoush, A Hallawa, A Peine, L Martin, A Schmeink IEEE/ACM Transactions on Audio, Speech, and Language Processing 31, 670-683, 2022 | 12 | 2022 |
| Management of ARDS: from ventilation strategies to intelligent technical support–connecting the dots J Kunze, S Fritsch, A Peine, O Maaßen, G Marx, J Bickenbach Trends in Anaesthesia and Critical Care 34, 50-58, 2020 | 8 | 2020 |
| The role of ribonuclease 1 and ribonuclease inhibitor 1 in acute kidney injury after open and endovascular thoracoabdominal aortic aneurysm repair E Zechendorf, A Gombert, T Bülow, N Frank, C Beckers, A Peine, ... Journal of clinical medicine 9 (10), 3292, 2020 | 6 | 2020 |
| A machine learning approach for the classification of disease risks in time series LB Fazlic, A Hallawa, M Dziubany, M Morgen, J Schneider, M Schacht, ... 2020 9th Mediterranean Conference on Embedded Computing (MECO), 1-5, 2020 | 5 | 2020 |
| Two-stage visual speech recognition for intensive care patients H Laux, A Hallawa, JCS Assis, A Schmeink, L Martin, A Peine Scientific Reports 13 (1), 928, 2023 | 4 | 2023 |
| Künstliche Intelligenz und maschinelles Lernen in der intensivmedizinischen Forschung und klinischen Anwendung. A Peine, C Lütge, F Poszler, L Celi, O Schöffski, G Marx, L Martin Anaesthesiologie & Intensivmedizin, 2020 | 4 | 2020 |
| Predicting abnormalities in laboratory values of patients in the intensive care unit using different deep learning models: Comparative study A Ayad, A Hallawa, A Peine, L Martin, LB Fazlic, G Dartmann, G Marx, ... JMIR Medical Informatics 10 (8), e37658, 2022 | 3 | 2022 |
| Perception of the COVID-19 pandemic among pneumology professionals in Germany A Peine, P Paffenholz, M Hellmich, L Martin, C Roderburg, A Heidenreich, ... Pneumologie (Stuttgart, Germany) 75 (4), 284-292, 2020 | 3 | 2020 |
| Artificial intelligence: challenges and applications in intensive care medicine L Martin, A Peine, M Gronholz, G Marx, J Bickenbach Anasthesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie: AINS 57 …, 2022 | 2 | 2022 |
| Künstliche Intelligenz: Herausforderungen und Nutzen in der Intensivmedizin L Martin, A Peine, M Gronholz, G Marx, J Bickenbach AINS-Anästhesiologie· Intensivmedizin· Notfallmedizin· Schmerztherapie 57 …, 2022 | 2 | 2022 |
Anke Schmeink (nee Feiten)RWTH Aachen UniversityAdresse e-mail validée de umic.rwth-aachen.de
