Johannes Allgaier

kurzer Lebenslauf

wissenschaftliche Schwerpunkte

Machine Learning, Data Science

Hauptpublikationen der letzten Jahre

Beierle F, Allgaier J, Stupp C, Keil T, Schlee W, Schobel J, Vogel C, Haug F, Haug J, Holfelder M, Langguth B, Langguth J, Riens B, King R, Mulansky L, Schickler M, Stach M, Heuschmann P, Wildner M, Greger H, Reichert M, Kestler HA, Pryss R
Self-Assessment of Having COVID-19 With the Corona Check Mhealth App
IEEE J Biomed Health Inform. 2023 Apr 6;PP. doi: 10.1109/JBHI.2023.3264999 

Allgaier J, Schlee W, Probst T, Pryss R
Prediction of Tinnitus Perception Based on Daily Life MHealth Data Using Country Origin and Season
J. Clin. Med. 2022, 11(15), 4270; https://doi.org/10.3390/jcm11154270

Landauer, J., Hoppenstedt, B., & Allgaier, J.
Image Segmentation To Locate Ancient Maya Architectures Using Deep Learning.

J. Allgaier, P. Neff, W. Schlee, S. Schoisswohl and R. Pryss.
Deep Learning End-to-End Approach for the Prediction of Tinnitus based on EEG Data.
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021, pp. 816-819, doi: 10.1109/EMBC46164.2021.9629964.

Fleischer, A., Heimeshoff, L., Allgaier, J., Jordan, K., Gelbrich, G., Pryss, R., ... & Rasche, L. (2021).
Is PFS the Right Endpoint to Assess Outcome of Maintenance Studies in Multiple Myeloma? Results of a Patient Survey Highlight Quality-of-Life As an Equally Important Outcome Measure.
Blood, 138, 836

Beierle, F.; Schobel, J.; Vogel, C.; Allgaier, J.; Mulansky, L.; Haug, F.; Haug, J.; Schlee, W.; Holfelder, M.; Stach, M.; Schickler, M.; Baumeister, H.; Cohrdes, C.; Deckert, J.; Deserno, L.; Edler, J.-S.; Eichner, F.A.; Greger, H.; Hein, G.; Heuschmann, P.; John, D.; Kestler, H.A.; Krefting, D.; Langguth, B.; Meybohm, P.; Probst, T.; Reichert, M.; Romanos, M.; Störk, S.; Terhorst, Y.; Weiß, M.; Pryss, R.
Corona Health—A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic.
Int. J. Environ. Res. Public Health 2021, 18, 7395. https://doi.org/10.3390/ijerph18147395

Schlee, W., Schoisswohl, S., Staudinger, S., Schiller, A., Lehner, A., Langguth, B., Schecklmann, M., Simoes, J., Neff, P., Marcrum, S. C., Spiliopoulou, M., Niemann, U., Schleicher, M., Unnikrishnan, V., Puga, C., Mulansky, L., Pryss, R., Vogel, C., Allgaier, J., ... Kikidis, D. (2021).
Towards a unification of treatments and interventions for tinnitus patients: The EU research and innovation action UNITI.
In W. Schlee, B. Langguth, T. Kleinjung, S. Vanneste, & D. De Ridder (Eds.), Tinnitus - An Interdisciplinary Approach Towards Individualized Treatment: From Heterogeneity to Personalized Medicine (pp. 441-451). (Progress in Brain Research; Vol. 260). Elsevier B.V.. https://doi.org/10.1016/bs.pbr.2020.12.005

Kammerer, Klaus and Hoppenstedt, Burkhard and Pryss, Rüdiger and Stökler, Steffen and Allgaier, Johannes and Reichert, Manfred (2019)
Anomaly Detections for Manufacturing Systems Based on Sensor Data—Insights into Two Challenging Real-World Production Settings.
Sensors, 19(24), MDPI, 10.3390/s19245370.