Automatic Recognition of Epileptiform EEG Abnormalities. - Alexander Brenner; Ekaterina Kutafina; Stephan M. Jonas (MIE, 2018)

Towards Interpretable Machine Learning in EEG Analysis. - Maged Mortaga; Alexander Brenner; Ekaterina Kutafina (GMDS, 2021)

Tracking of Mental Workload with a Mobile EEG Sensor. - Ekaterina Kutafina; Anne Heiligers; Radomir Popovic; Alexander Brenner; Bernd Hankammer; Stephan M. Jonas; Klaus Mathiak; Jana Zweerings (Sensors, 2021)

Consistency of Feature Importance Algorithms for Interpretable EEG Abnormality Detection. - Felix Knispel; Alexander Brenner; Rainer Röhrig; Yvonne Weber; Julian Varghese; Ekaterina Kutafina (GMDS, 2022)

Utilizing a Non-Motor Symptoms Questionnaire and Machine Learning to Differentiate Movement Disorders. - Alexander Brenner; Lucas Plagwitz; Michael Fujarski; Tobias Warnecke; Julian Varghese (MIE, 2022)

Prediction of Acute Kidney Injury in the Intensive Care Unit: Preliminary Findings in a European Open Access Database. - Michael Fujarski; Christian Porschen; Lucas Plagwitz; Alexander Brenner; Narges Ghoreishi; Patrick Thoral; Harm-Jan de Grooth; Paul W. G. Elbers; Raphael Weiss; Melanie Meersch; Alexander Zarbock; Thilo Caspar von Groote; et al. (MIE, 2022)

Supporting AI-Explainability by Analyzing Feature Subsets in a Machine Learning Model. - Lucas Plagwitz; Alexander Brenner; Michael Fujarski; Julian Varghese (MIE, 2022)

Reducing a complex two-sided smartwatch examination for Parkinson's Disease to an efficient one-sided examination preserving machine learning accuracy. - Alexander Brenner; Michael Fujarski; Tobias Warnecke; Julian Varghese (CoRR, 2022)

Subgroup discovery of Parkinson's Disease by utilizing a multi-modal smart device system. - Catharina Marie van Alen; Alexander Brenner; Tobias Warnecke; Julian Varghese (CoRR, 2022)

Classification of Parkinson's Disease from Voice - Analysis of Data Selection Bias. - Alexander Brenner; Catharina Marie van Alen; Lucas Plagwitz; Julian Varghese (MIE, 2023)

Mixed Reality in Medical Education - Introduction of a Practical Course Module. - Alexander Brenner; Yannik Warnecke; Michael Fujarski; Julian Varghese (MIE, 2024)

Concept-based AI interpretability in physiological time-series data: Example of abnormality detection in electroencephalography. - Alexander Brenner; Felix Knispel; Florian P. Fischer; Peter Rossmanith; Yvonne Weber; Henner Koch; Rainer Röhrig; Julian Varghese; Ekaterina Kutafina (Comput. Methods Programs Biomed., 2024)

The Rlign Algorithm for Enhanced Electrocardiogram Analysis through R-Peak Alignment for Explainable Classification and Clustering. - Lucas Plagwitz; Lucas Bickmann; Michael Fujarski; Alexander Brenner; Warnes Gobalakrishnan; Lars Eckardt; Antonius Büscher; Julian Varghese (CoRR, 2024)