Dr. Johannes Allgaier
Dr. rer. nat. Johannes Allgaier
Am Schwarzenberg 15, Haus A15
Telefon:
+49 931-201 46407
Fax:
+49 931-201 647310
![](/fileadmin/_processed_/3/c/csm_allgaier_johannes_2_c3c4ca845b.jpg)
kurzer Lebenslauf
Seit 2024 | Postdoc am Institut für Medical Data Science an der Universität Würzburg |
2024 | Promotion zum Dr. rer. nat. (summa cum laude) |
2023 | Forschungsstipendium an der University of Michigan, USA |
2020-2024 | Wissenschaftlicher Mitarbeiter am Institut für Klinische Epidemiologie und Biometrie an der Universität Würzburg |
2017-2020 | Studium M.Sc. Wirtschaftswissenschaften an der Universität Ulm und National Taiwan University of Science and Technology |
2014-2017 | Studium B.Sc. Wirtschaftswissenschaften an der Universität Ulm |
wissenschaftliche Schwerpunkte
Explainable Machine Learning, Data Science, Statistics, Machine Learning Pipelines
Hauptpublikationen der letzten Jahre
2023[ to top ]
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Self-Assessment of Having COVID-19 With the Corona Check Mhealth App. IEEE J Biomed Health Inform. 2023;Pp..
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How does the model make predictions? A systematic literature review on the explainability power of machine learning in healthcare. Artif Intell Med. 2023;143:102616..
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Predicting the presence of tinnitus using ecological momentary assessments. Scientific Reports [Internet]. 2023;13(1):8989. Available from: https://doi.org/10.1038/s41598-023-36172-7.
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2022[ to top ]
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Prediction of Tinnitus Perception Based on Daily Life MHealth Data Using Country Origin and Season. Journal of Clinical Medicine [Internet]. 2022;11(15):4270. Available from: https://www.mdpi.com/2077-0383/11/15/4270.
2021[ to top ]
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Predicting the gender of individuals with tinnitus based on daily life data of the TrackYourTinnitus mHealth platform. Scientific Reports [Internet]. 2021;11(1):18375. Available from: https://doi.org/10.1038/s41598-021-96731-8.
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Using Big Data to Develop a Clinical Decision Support System for Tinnitus Treatment. In: Searchfield GD, Zhang J, editors. The Behavioral Neuroscience of Tinnitus [Internet]. Cham: Springer International Publishing; 2021. pp. 175-89. Available from: https://doi.org/10.1007/7854_2021_229.
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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 [Internet]. 2021;138:836. Available from: https://www.sciencedirect.com/science/article/pii/S000649712102824X.
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Deep Learning End-to-End Approach for the Prediction of Tinnitus based on EEG Data. In: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2021. pp. 816-9..
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Towards a unification of treatments and interventions for tinnitus patients: The EU research and innovation action UNITI. In: Schlee W, Langguth B, Kleinjung T, Vanneste S, De Ridder D, editors. Progress in Brain Research [Internet]. Elsevier; 2021. pp. 441-5. Available from: https://www.sciencedirect.com/science/article/pii/S0079612320302351.
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Corona Health—A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic. International Journal of Environmental Research and Public Health [Internet]. 2021;18(14):7395. Available from: https://www.mdpi.com/1660-4601/18/14/7395.
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Image Segmentation To Locate Ancient Maya Architectures Using Deep Learning. In: Kocev D, Simidjievski N, Kostovska A, Dimitrovski I, Kokalj Z, editors. Discover the mysteries of the maya. Jožef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia; 2021. p. 7..
2019[ to top ]
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Anomaly Detections for Manufacturing Systems Based on Sensor Data—Insights into Two Challenging Real-World Production Settings. Sensors [Internet]. 2019;19(24):5370. Available from: https://www.mdpi.com/1424-8220/19/24/5370.