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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)A cost-based multi-layer network approach for the discovery of patient phenotypes, , , and . International Journal of Data Science and Analytics, (July 2023)The statistical analysis plan for the unification of treatments and interventions for tinnitus patients randomized clinical trial (UNITI-RCT), , , , , , , , , and 31 other author(s). Trials, 24 (1): 472 (2023)Juxtaposing Medical Centers Using Different Questionnaires Through Score Predictors, , , , , , , , , and 1 other author(s). Frontiers in Neuroscience, (March 2022)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)Leveraging the potential of multi-layer networks for subgroup discovery.. Otto-von-Guericke University Magdeburg, Germany, (2024)Training and Validating a Treatment Recommender with Partial Verification Evidence., , , , , , , , , and 4 other author(s). CoRR, (2024)Discovery of Patient Phenotypes through Multi-layer Network Analysis on the Example of Tinnitus., , , , , and . DSAA, page 1-10. IEEE, (2021)A Similarity-Guided Framework for Error-Driven Discovery of Patient Neighbourhoods in EMA Data., , , , , , and . IDA, volume 13876 of Lecture Notes in Computer Science, page 459-471. Springer, (2023)A cost-based multi-layer network approach for the discovery of patient phenotypes., , , and . CoRR, (2022)