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Johannes Allgaier
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2020 – today
- 2024
- [b1]Johannes Allgaier:
Machine Learning Explainability on Multi-Modal Data using Ecological Momentary Assessments in the Medical Domain (Erklärbarkeit von maschinellem Lernen unter Verwendung multi-modaler Daten und Ecological Momentary Assessments im medizinischen Sektor). Würzburg University, Germany, 2024 - [j4]Johannes Allgaier
, Rüdiger Pryss
Cross-Validation Visualized: A Narrative Guide to Advanced Methods. Mach. Learn. Knowl. Extr. 6(2): 1378-1388 (2024) - 2023
- [j3]Johannes Allgaier, Lena Mulansky, Rachel Lea Draelos, Rüdiger Pryss:
How does the model make predictions? A systematic literature review on the explainability power of machine learning in healthcare. Artif. Intell. Medicine 143: 102616 (2023) - [j2]Felix Beierle
Self-Assessment of Having COVID-19 With the Corona Check mHealth App. IEEE J. Biomed. Health Informatics 27(6): 2794-2805 (2023) - 2021
- [c1]Johannes Allgaier, Patrick Neff
Deep Learning End-to-End Approach for the Prediction of Tinnitus based on EEG Data*. EMBC 2021: 816-819 - [i1]Felix Beierle, Johannes Schobel, Carsten Vogel, Johannes Allgaier, Lena Mulansky, Fabian Haug, Julian Haug, Winfried Schlee, Marc Holfelder, Michael Stach, Marc Schickler, Harald Baumeister, Caroline Cohrdes, Jürgen Deckert, Lorenz Deserno, Johanna-Sophie Edler, Felizitas A. Eichner, Helmut Greger, Grit Hein, Peter Heuschmann, Dennis John, Hans A. Kestler, Dagmar Krefting, Berthold Langguth, Patrick Meybohm, Thomas Probst, Manfred Reichert, Marcel Romanos, Stefan Störk, Yannik Terhorst, Martin Weiß, Rüdiger Pryss:
Corona Health - A Study- and Sensor-based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic. CoRR abs/2106.03386 (2021)
2010 – 2019
- 2019
- [j1]Klaus Kammerer
Anomaly Detections for Manufacturing Systems Based on Sensor Data - Insights into Two Challenging Real-World Production Settings. Sensors 19(24): 5370 (2019)
Coauthor Index
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last updated on 2024-10-16 20:33 CEST by the dblp team
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