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Edge AI-deployed DIGItal Twins for PREDICTing disease progression and need for early intervention in infectious and cardiovascular diseases beyond COVID-19

Descrizione del progetto

Cerotti IA per prevedere la progressione delle malattie in tempo reale

La COVID-19 è associata a molti sintomi diversi, da mal di gola e perdita del gusto a sintomi più seri come l’insufficienza polmonare. Esiste un modo per prevedere quanto sarà seria la malattia prima che si manifesti? Il progetto DIGIPREDICT, finanziato dall’UE, sta sviluppando un sistema basato sull’IA in grado di prevedere se i pazienti affetti da COVID-19 svilupperanno complicazioni cardiovascolari gravi e, nel lungo periodo, individuerà la probabilità di insorgenza di malattie infiammatorie. Nello specifico, sarà proposto il primo gemello digitale unico nel suo genere che consisterà in un cerotto intelligente con tecnologia integrata per la raccolta di un insieme di dati medici. Sarà così possibile monitorare l’efficacia del trattamento in tempo reale.

Obiettivo

The 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.

Campo scientifico (EuroSciVoc)

Parole chiave

Programma(i)

Argomento(i)

Meccanismo di finanziamento

RIA - Research and Innovation action

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(si apre in una nuova finestra) H2020-FETPROACT-2018-2020

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Coordinatore

ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Contributo netto dell'UE
€ 1 158 355,00
Indirizzo
BATIMENT CE 3316 STATION 1
1015 Lausanne
Svizzera
Regione
Schweiz/Suisse/Svizzera Région lémanique Vaud
Tipo di attività
Higher or Secondary Education Establishments
Collegamenti
Costo totale
€ 1 158 355,00

Partecipanti (9)