Ziekenhuisgroep Twente
Ziekenhuisgroep Twente
2 Projects, page 1 of 1
assignment_turned_in Project2019 - 9999Partners:Technische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Wiskunde en Informatica - Department of Mathematics and Computer Science, Informatica, Technische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Wiskunde en Informatica - Department of Mathematics and Computer Science, Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Philips Research Eindhoven, Technische Universiteit Eindhoven - Eindhoven University of Technology +10 partnersTechnische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Wiskunde en Informatica - Department of Mathematics and Computer Science, Informatica,Technische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Wiskunde en Informatica - Department of Mathematics and Computer Science,Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS),Philips Research Eindhoven,Technische Universiteit Eindhoven - Eindhoven University of Technology,Ziekenhuisgroep Twente,Universiteit Twente,Technische Universiteit Eindhoven - Eindhoven University of Technology,Roessingh Concern, Roessingh Research and Development,Ziekenhuisgroep Twente,Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Interdiscipline Creative Technology, Biomedical Signals and Systems (BSS),Philips Research Eindhoven,Technische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Wiskunde en Informatica - Department of Mathematics and Computer Science, Informatica, Information Systems (IS),Roessingh Concern,Technische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Wiskunde en Informatica - Department of Mathematics and Computer Science, Informatica, Information Systems (IS), Data Mining (DM)Funder: Netherlands Organisation for Scientific Research (NWO) Project Code: 628.011.021Our increased life expectancy unfortunately goes hand in hand with an increased number of years living with chronic conditions. These conditions cannot be cured, but both the development of comorbidities and the quality of life are strongly influenced by proper self-management and by deploying a healthy lifestyle. In the EDIC project, we develop a novel data-driven artificial coaching platform that supports chronically ill patients in making optimal lifestyle decisions. We bring in expertise in data mining, telemedicine, e-coaching, behavioral sciences and domain expertise, and particularly focus on the bariatric and diabetes-2 patient population.
more_vert assignment_turned_in Project2022 - 9999Partners:Universiteit Twente, Technical Medical Centre, Developmental BioEngineering (DBE), Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Applied Mathematics, Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Radboud universitair medisch centrum, Orthopaedic Research Laboratory, Technische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Biomedische Technologie - Department of Biomedical Engineering, Biomechanics & Tissue Engineering +29 partnersUniversiteit Twente, Technical Medical Centre, Developmental BioEngineering (DBE),Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Applied Mathematics,Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS),Radboud universitair medisch centrum, Orthopaedic Research Laboratory,Technische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Biomedische Technologie - Department of Biomedical Engineering, Biomechanics & Tissue Engineering,Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Interdiscipline Creative Technology, Biomedical Signals and Systems (BSS),Medisch Spectrum Twente,Technische Universiteit Delft, Faculteit Mechanical Engineering (ME), Biomechanical Engineering,Technische Universiteit Eindhoven - Eindhoven University of Technology, Faculteit Wiskunde en Informatica - Department of Mathematics and Computer Science,Erasmus MC, Huisartsgeneeskunde,Technische Universiteit Eindhoven - Eindhoven University of Technology,Technische Universiteit Delft, Faculteit Mechanical Engineering (ME), Biomechanical Engineering, Biomaterials & Tissue Biomechanics,Technische Universiteit Eindhoven - Eindhoven University of Technology,Erasmus MC,Erasmus MC, Interne Geneeskunde, Endocrinologie,LUMC,Saxion,Universiteit Twente, Faculty of Science and Technology (TNW),Erasmus MC, Keel- Neus- en Oorheelkunde,Leids Universitair Medisch Centrum, Medical Statistics and Biofinformatics,Radboud universitair medisch centrum,Universiteit Twente, Faculty of Behavioural, Management and Social sciences (BMS), Health Technology and Services Research,Rotterdam University of Applied Sciences,Technische Universiteit Delft, Faculteit Technische Natuurwetenschappen, NanoScience - Kavli Institute of Nanoscience Delft, Department of Bionanoscience,Technische Universiteit Delft,Medisch Spectrum Twente,Universiteit Twente,Universiteit Twente,Erasmus MC, Radiologie,Ziekenhuisgroep Twente,Erasmus MC, Orthopaedie,Technische Universiteit Delft,Ziekenhuisgroep Twente,Erasmus MCFunder: Netherlands Organisation for Scientific Research (NWO) Project Code: NWA.1389.20.009Osteoarthritis is a painful, disabling joint disease that affects millions of people. There is no cure for Osteoarthritis. Patients are encouraged to stay physically active, but the optimal joint loading for the individual patient is not known. The LoaD project aims to obtain this knowledge and develop personalised support strategies for use in daily life.
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