000468642 001__ 468642
000468642 005__ 20230214181022.0
000468642 0247_ $$2CORDIS$$aG:(EU-Grant)101017915$$d101017915
000468642 0247_ $$2CORDIS$$aG:(EU-Call)H2020-FETPROACT-2020-2$$dH2020-FETPROACT-2020-2
000468642 0247_ $$2originalID$$acorda__h2020::101017915
000468642 035__ $$aG:(EU-Grant)101017915
000468642 150__ $$aEdge AI-deployed DIGItal Twins for PREDICTing disease progression and need for early intervention in infectious and cardiovascular diseases beyond COVID-19$$y2021-01-01 - 2024-12-31
000468642 372__ $$aH2020-FETPROACT-2020-2$$s2021-01-01$$t2024-12-31
000468642 450__ $$aDIGIPREDICT$$wd$$y2021-01-01 - 2024-12-31
000468642 5101_ $$0I:(DE-588b)5098525-5$$2CORDIS$$aEuropean Union
000468642 680__ $$aThe interplay between viral infection, host response, development of (hyper)inflammation and cardiovascular injury in COVID-19 is currently poorly understood which makes it difficult to predict which patients remain with mild symptoms only and which patients rapidly develop multi organ failure. The solution offered by DIGIPREDICT is an Edge Artificial Intelligence (AI) based, high-tech personalized computational and physical Digital Twin vehicle representing patient-specific (patho)physiology, with embedded disease progression prediction capability, focusing on COVID-19 and beyond. DIGIPREDICT proposes the first of its kind Digital Twin, designed, developed and calibrated on i) patient measurements of various Digital Biomarkers and their interaction, ii) Organ-On-Chips (OoCs) as physical counterpart using patient blood for personalized screening and iii) integration of those physiological readouts using AI at Edge technologies. The final goal is to identify and validate patient-specific dynamic digital fingerprints of complex disease state and prediction of the progression as a basis for assistive tools for medical doctors and patients. Using and improving state-of-the-art OoCs and Digital Biomarkers (for physiology and biomarkers in interstitial fluid) we will measure detailed response to viral infection. By closely monitoring the response with wearable multi-modal Edge AI patches, we aim to predict in near real-time the progression of the disease, support early clinical decision and to propose patient-specific therapy using existing drugs. We will combine scientific and technical excellence in a highly multi- and inter-disciplinary project, bringing together medical, biological, electronical, computer, signal processing and social science communities around Europe to setup Digital Twin at Edge. We will enable an Edge-to-Cloud vision, significantly advancing current state of the art and setting up a new European community for researching and applying Digital Twins.
000468642 909CO $$ooai:juser.fz-juelich.de:900331$$pauthority$$pauthority:GRANT
000468642 909CO $$ooai:juser.fz-juelich.de:900331
000468642 980__ $$aG
000468642 980__ $$aCORDIS
000468642 980__ $$aAUTHORITY