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Predicting the gender of individuals with tinnitus based on daily life data of the TrackYourTinnitus mHealth platform

, , , , and . Scientific Reports, 11 (1): 18375 (2021)
DOI: 10.1038/s41598-021-96731-8

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Predicting the presence of tinnitus using ecological momentary assessments, , , , , , , , and . Scientific Reports, 13 (1): 8989 (2023)Deep Learning End-to-End Approach for the Prediction of Tinnitus based on EEG Data*., , , , and . EMBC, page 816-819. IEEE, (2021)Predicting the gender of individuals with tinnitus based on daily life data of the TrackYourTinnitus mHealth platform, , , , and . Scientific Reports, 11 (1): 18375 (2021)Corona Health - A Study- and Sensor-based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic., , , , , , , , , and 22 other author(s). CoRR, (2021)Prediction of Tinnitus Perception Based on Daily Life MHealth Data Using Country Origin and Season, , , and . Journal of Clinical Medicine, 11 (15): 4270 (2022)Towards a unification of treatments and interventions for tinnitus patients: The EU research and innovation action UNITI, , , , , , , , , and 70 other author(s). 260, page 441-451. Elsevier, (2021)Anomaly Detections for Manufacturing Systems Based on Sensor Data - Insights into Two Challenging Real-World Production Settings., , , , , and . Sensors, 19 (24): 5370 (2019)Using Big Data to Develop a Clinical Decision Support System for Tinnitus Treatment, , , , , , , , , and 9 other author(s). page 175-189. Springer International Publishing, Cham, (2021)How does the model make predictions? A systematic literature review on the explainability power of machine learning in healthcare., , , and . Artif. Intell. Medicine, (September 2023)Cross-Validation Visualized: A Narrative Guide to Advanced Methods., and . Mach. Learn. Knowl. Extr., 6 (2): 1378-1388 (June 2024)