WP4 - Statistical Modeling of Health Data
The DMMH system collects a rich source of data and information on the overall behavior and mental state of individuals throughout the study. WP4 is dedicated to analyzing this data and extracting relevant patterns, as well as to analyzing crucial predictive features to build statistical models that can be used to guide clinical care. WP4 uses simple low level statistics, as well as modern state-of-the-art deep time series models, based on recurrent neural networks for the prediction of individual health trajectories.
The people involved
Dr. Georgia Koppe
Head of research group Computational Psychiatry, focused on the data analytics of IMMERSE (WP4)
Prof. Daniel Dürstewitz
Head of dept. of Theoretical Neuroscience, focused on the data analytics of IMMERSE (WP4)
Prof. Peter Kuppens
Professor at the Research group of Quantitative Psychology and Individual Differences, provides guidance on developing data visualisation and analyses relevant for clinicians (WP4)
This project has received funding from the European Union’s Horizon 2020 research and innovation Programme under grant agreement 945263 (IMMERSE). This website reflects only the authors' view and the European Commission is not responsible for any use that may be made of the information it contains
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