Descripción del proyecto
Parches de inteligencia artificial para predecir la evolución de la enfermedad en tiempo real
La COVID-19 se asocia con multitud de síntomas diferentes, desde dolor de garganta y pérdida del sentido del gusto hasta otros más graves como la insuficiencia pulmonar. ¿Hay alguna manera de predecir la gravedad de la enfermedad cuando se manifiesta por primera vez? El proyecto financiado con fondos europeos DIGIPREDICT está desarrollando un sistema basado en inteligencia artificial que permite predecir si los pacientes con COVID-19 desarrollarán complicaciones cardiovasculares graves y, a largo plazo, detectar la posible manifestación de una enfermedad inflamatoria intestinal. En concreto, propone el primer gemelo digital de este tipo, que consistirá en un parche inteligente con tecnología integrada para recopilar diversos datos médicos. Esto permitirá realizar un seguimiento de lo bien que está funcionando el tratamiento.
Objetivo
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.
Ámbito científico
- medical and health sciencesbasic medicinephysiologypathophysiology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsignal processing
- natural sciencescomputer and information sciencesartificial intelligenceedge artificial Intelligence
- medical and health scienceshealth sciencesinfectious diseasesRNA virusescoronaviruses
- medical and health sciencesclinical medicinecardiologycardiovascular diseases
Palabras clave
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-FETPROACT-2020-2
Régimen de financiación
RIA - Research and Innovation actionCoordinador
1015 Lausanne
Suiza