UNITI results 20231201

UNITI results

UNITI project finished in September 2023. It’s overall aim was to deliver a predictive computational model based on existing and longitudinal data attempting to address the question which treatment approach is optimal for a specific patient based on specific parameters. Clinical, epidemiological, medical, genetic and audiological data, including signals reflecting ear-brain communication, were analysed from existing databases. Predictive factors for different patient groups were extracted and their prognostic relevance were tested in a randomized controlled trial (RCT) in which different groups of patients underwent a combination of therapies targeting the auditory and central nervous systems.

Click here to learn more about the UNITI results.



EMA app UNITIWe are happy to announce that we have a new paper published in Frontiers in Neuroscience: "Predicting Ecological Momentary Assessments in an App for Tinnitus by Learning From Each User's Stream With a Contextual Multi-Armed Bandit". 

Our main findings are that for EMA prediction the entity-centric predictors should be preferred over a user-insensitive global model, and  that the choice of EMA items should be further investigated, because some items are answered more rarely than others. Albeit our CMAB-based prediction workflow is robust to differences in exposition and in interaction intensity, experimentators that design studies with mHealth apps should be prepared to quantify and closely monitor differences in the intensity of user-app interaction, since users with many interactions may have a disproportionate influence on global models.

More information about this publication can be found here: https://www.frontiersin.org/articles/10.3389/fnins.2022.836834/.

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Key Facts

Data and analysis scripts of the UNITI-RCT results are currently available upon request (stefan.schoisswohl@klinik.uni-regensburg.de).

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