About The Project
Topic: SC1-PM-17-2017: Personalised computer models and in-silico systems for well-being, RIA action, σε συνεργασία με το ΕΘΝΙΚΟ ΚΕΝΤΡΟ ΕΡΕΥΝΑΣ & ΤΕΧΝΟΛΟΓΙΚΗΣ ΑΝΑΠΤΥΞΗΣ / ΕΚΕΤΑ (CERTH).
Role in the project: Development of data mining techniques for knowledge discovery using interpretable rule-based models to provide insights for the understanding of OA disease development and its progression. Identification of patient-specific significant risk factors associated with the onset as well as factors related to OA progression using computational efficient Feature Selection algorithms.
Design and implementation of personalized predictive Decision Support (DS) models that address specific OA stages in the disease continuum of a patient (DS-early, DS-mild, DS-mod and DS-treat).