11 Predicting comorbidities of epilepsy patients using big data from Electronic Health Records augmented with biomedical knowledge Thomas Linden ( Fraunhofer SCAI, Bonn-Aachen International Center for Information Technology )
12 Identifying, predicting and validating subtypes of Parkinson Disease progression using machine learning Ashar Ahmad(University of Bonn)
13 Generative Artificial Intelligence Approaches for Modeling of Multimodal Longitudinal Clinical Studies and Simulation of Virtual Cohorts Philipp Wendland (Fraunhofer SCAI, University of Applied Sciences Koblenz)
14 Machine learning classification of Alzheimer’s disease: Diagnostic Prediction Using Cognitive and Functional Domains Mohamed Aborageh (Fraunhofer SCAI)
15 Robust prediction of age from MEG/EEG signals without biophysical source modeling David Sabbagh (INRIA)
16 Lack of support for a common cause hypothesis of visuo-cognitive aging: multivariate statistical analysis on the SilverSight follow-up cohort study Angelo Arleo (CNRS Vision Institute)
17 Deep learning models for brain age estimation Lara Dular (University of Ljubljana, Faculty of Electrical Engineering, Laboratory of Imaging Technologies)
18 The scored events model: Subtype and Stage Inference (SuStaIn) for visual ratings, clinical scores and other ordinal data Alexandra Young (Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King′s College London)
19 Modelling longitudinal binary data in Parkinson Pierre-Emmanuel Poulet (ARAMIS Lab)
20 Modeling the progression of Parkinson’s Disease : comparison of subjects with and without Sleep Disorders Raphaël Couronné (UPMC/INRIA)
21 Predicted brain age as a cognitive biomarker in Multiple Sclerosis Stijn Denissen (UZ Brussels/icometrix)