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Parsimonious predictors for medical decision support: Minimizing the set of questionnaires used for tinnitus outcome prediction

, , , , , and . Expert Systems with Applications, (April 2023)
DOI: 10.1016/j.eswa.2023.122336

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Expect the gap: A recommender approach to estimate the absenteeism of self-monitoring mHealth app users., , , , and . DSAA, page 1-10. IEEE, (2022)Parsimonious predictors for medical decision support: Minimizing the set of questionnaires used for tinnitus outcome prediction, , , , , and . Expert Systems with Applications, (April 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)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)Active feature acquisition on data streams under feature drift, , , , , and . Annals of Telecommunications, (Jul 8, 2020)The Effect of Non-Personalised Tips on the Continued Use of Self-Monitoring mHealth Applications, , , , , , , , and . Brain Sciences, 10 (12): 924 (2020)Understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring, , , , , , , and . Scientific Reports, (December 2020)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)