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Expect the gap: A recommender approach to estimate the absenteeism of self-monitoring mHealth app users., , , , и . DSAA, стр. 1-10. IEEE, (2022)Juxtaposing Medical Centers Using Different Questionnaires Through Score Predictors, , , , , , , , , и 1 other автор(ы). Frontiers in Neuroscience, (марта 2022)Using Big Data to Develop a Clinical Decision Support System for Tinnitus Treatment, , , , , , , , , и 9 other автор(ы). стр. 175-189. Springer International Publishing, Cham, (2021)Parsimonious predictors for medical decision support: Minimizing the set of questionnaires used for tinnitus outcome prediction, , , , , и . Expert Systems with Applications, (апреля 2023)A Similarity-Guided Framework for Error-Driven Discovery of Patient Neighbourhoods in EMA Data., , , , , , и . IDA, том 13876 из Lecture Notes in Computer Science, стр. 459-471. Springer, (2023)Discovery of Patient Phenotypes through Multi-layer Network Analysis on the Example of Tinnitus., , , , , и . DSAA, стр. 1-10. IEEE, (2021)Understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring, , , , , , , и . Scientific Reports, (декабря 2020)Active feature acquisition on data streams under feature drift, , , , , и . Annals of Telecommunications, (08.07.2020)The statistical analysis plan for the unification of treatments and interventions for tinnitus patients randomized clinical trial (UNITI-RCT), , , , , , , , , и 31 other автор(ы). Trials, 24 (1): 472 (2023)The Effect of Non-Personalised Tips on the Continued Use of Self-Monitoring mHealth Applications, , , , , , , , и . Brain Sciences, 10 (12): 924 (2020)