| Tracking of mental workload with a mobile EEG sensor E Kutafina, A Heiligers, R Popovic, A Brenner, B Hankammer, SM Jonas, ... Sensors 21 (15), 5205, 2021 | 23 | 2021 |
| Automatic recognition of epileptiform EEG abnormalities A Brenner, E Kutafina, SM Jonas Building Continents of Knowledge in Oceans of Data: The Future of Co-Created …, 2018 | 11 | 2018 |
| Towards interpretable machine learning in EEG analysis M Mortaga, A Brenner, E Kutafina German Medical Data Sciences 2021: Digital Medicine: Recognize–Understand …, 2021 | 10 | 2021 |
| Comparison of mobile and clinical EEG sensors through resting state simultaneous data collection E Kutafina, A Brenner, Y Titgemeyer, R Surges, S Jonas PeerJ 8, e8969, 2020 | 10 | 2020 |
| Supporting AI-explainability by analyzing feature subsets in a machine learning model L Plagwitz, A Brenner, M Fujarski, J Varghese Challenges of Trustable AI and Added-Value on Health, 109-113, 2022 | 4 | 2022 |
| Machine Learning in the Parkinson’s disease smartwatch (PADS) dataset J Varghese, A Brenner, M Fujarski, CM van Alen, L Plagwitz, T Warnecke npj Parkinson's Disease 10 (1), 9, 2024 | 2 | 2024 |
| Consistency of Feature Importance Algorithms for Interpretable EEG Abnormality Detection F Knispel, A Brenner, R Röhrig, Y Weber, J Varghese, E Kutafina German Medical Data Sciences 2022–Future Medicine: More Precise, More …, 2022 | 2 | 2022 |
| Prediction of acute kidney injury in the intensive care unit: preliminary findings in a European open access database M Fujarski, C Porschen, L Plagwitz, A Brenner, N Ghoreishi, P Thoral, ... Challenges of Trustable AI and Added-Value on Health, 139-140, 2022 | 2 | 2022 |
| Utilizing a non-motor symptoms questionnaire and machine learning to differentiate movement disorders A Brenner, L Plagwitz, M Fujarski, T Warnecke, J Varghese Challenges of Trustable AI and Added-Value on Health, 104-108, 2022 | 2 | 2022 |
| Classification of Parkinson’s Disease from Voice–Analysis of Data Selection Bias A Brenner, CM Van Alen, L Plagwitz, J Varghese Caring is Sharing–Exploiting the Value in Data for Health and Innovation …, 2023 | 1 | 2023 |
| Reducing a complex two-sided smartwatch examination for Parkinson's Disease to an efficient one-sided examination preserving machine learning accuracy A Brenner, M Fujarski, T Warnecke, J Varghese arXiv preprint arXiv:2205.05361, 2022 | 1 | 2022 |
| Author Correction: Machine Learning in the Parkinson’s disease smartwatch (PADS) dataset J Varghese, A Brenner, M Fujarski, CM van Alen, L Plagwitz, T Warnecke npj Parkinson's Disease 10 (1), 92, 2024 | | 2024 |
| Smartwatch Versus Routine Tremor Documentation: Descriptive Comparison CM van Alen, A Brenner, T Warnecke, J Varghese JMIR Formative Research 8 (1), e51249, 2024 | | 2024 |
| Subgroup discovery of Parkinson's Disease by utilizing a multi-modal smart device system CM van Alen, A Brenner, T Warnecke, J Varghese arXiv preprint arXiv:2205.05961, 2022 | | 2022 |
| PADS-Parkinsons Disease Smartwatch dataset J Varghese, A Brenner, L Plagwitz, C van Alen, M Fujarski, T Warnecke | | |
Julian VargheseUniversity of Muenster在 uni-muenster.de 的电子邮件经过验证
