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Alexander Brenner

Showing results (1-10 of 18) with videos related to

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Studies in Health Technology and Informatics|September 21, 2021
Towards Interpretable Machine Learning in EEG AnalysisMaged Mortaga, Alexander Brenner, Ekaterina Kutafina
Studies in Health Technology and Informatics|April 22, 2018
Automatic Recognition of Epileptiform EEG AbnormalitiesAlexander Brenner, Ekaterina Kutafina, Stephan M Jonas
Studies in Health Technology and Informatics|May 25, 2022
Supporting AI-Explainability by Analyzing Feature Subsets in a Machine Learning ModelLucas Plagwitz, Alexander Brenner, Michael Fujarski, et al.
Studies in Health Technology and Informatics|August 23, 2024
Mixed Reality in Medical Education - Introduction of a Practical Course ModuleAlexander Brenner, Yannik Warnecke, Michael Fujarski, et al.
Peerj|May 12, 2020
Comparison of mobile and clinical EEG sensors through resting state simultaneous data collectionEkaterina Kutafina, Alexander Brenner, Yannic Titgemeyer, et al.
JMIR Formative Research|March 20, 2024
Smartwatch Versus Routine Tremor Documentation: Descriptive ComparisonCatharina Marie van Alen, Alexander Brenner, Tobias Warnecke, et al.
Studies in Health Technology and Informatics|May 19, 2023
Classification of Parkinson's Disease from Voice - Analysis of Data Selection BiasAlexander Brenner, Catharina Marie Van Alen, Lucas Plagwitz, et al.
International Journal of Medical Microbiology : IJMM|March 5, 2025
Validation of ML-algorithms for the prediction of positive urine cultures from flow cytometry routine data in patients with suspected bacteriuriaAlexander Brenner, Jutta Esser, Franziska Schuler, et al.
Studies in Health Technology and Informatics|May 25, 2022
Utilizing a Non-Motor Symptoms Questionnaire and Machine Learning to Differentiate Movement DisordersAlexander Brenner, Lucas Plagwitz, Michael Fujarski, et al.
Studies in Health Technology and Informatics|September 8, 2022
Consistency of Feature Importance Algorithms for Interpretable EEG Abnormality DetectionFelix Knispel, Alexander Brenner, Rainer Röhrig, et al.
Pageof 2

Showing results (1-10 of 18) with videos related to

Sort By:
Pageof 2
Studies in Health Technology and Informatics|September 21, 2021
Towards Interpretable Machine Learning in EEG AnalysisMaged Mortaga, Alexander Brenner, Ekaterina Kutafina
Studies in Health Technology and Informatics|April 22, 2018
Automatic Recognition of Epileptiform EEG AbnormalitiesAlexander Brenner, Ekaterina Kutafina, Stephan M Jonas
Studies in Health Technology and Informatics|May 25, 2022
Supporting AI-Explainability by Analyzing Feature Subsets in a Machine Learning ModelLucas Plagwitz, Alexander Brenner, Michael Fujarski, et al.
Studies in Health Technology and Informatics|August 23, 2024
Mixed Reality in Medical Education - Introduction of a Practical Course ModuleAlexander Brenner, Yannik Warnecke, Michael Fujarski, et al.
Peerj|May 12, 2020
Comparison of mobile and clinical EEG sensors through resting state simultaneous data collectionEkaterina Kutafina, Alexander Brenner, Yannic Titgemeyer, et al.
JMIR Formative Research|March 20, 2024
Smartwatch Versus Routine Tremor Documentation: Descriptive ComparisonCatharina Marie van Alen, Alexander Brenner, Tobias Warnecke, et al.
Studies in Health Technology and Informatics|May 19, 2023
Classification of Parkinson's Disease from Voice - Analysis of Data Selection BiasAlexander Brenner, Catharina Marie Van Alen, Lucas Plagwitz, et al.
International Journal of Medical Microbiology : IJMM|March 5, 2025
Validation of ML-algorithms for the prediction of positive urine cultures from flow cytometry routine data in patients with suspected bacteriuriaAlexander Brenner, Jutta Esser, Franziska Schuler, et al.
Studies in Health Technology and Informatics|May 25, 2022
Utilizing a Non-Motor Symptoms Questionnaire and Machine Learning to Differentiate Movement DisordersAlexander Brenner, Lucas Plagwitz, Michael Fujarski, et al.
Studies in Health Technology and Informatics|September 8, 2022
Consistency of Feature Importance Algorithms for Interpretable EEG Abnormality DetectionFelix Knispel, Alexander Brenner, Rainer Röhrig, et al.
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