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Personalised Health Monitoring and Decision Support Based on Artificial Intelligence and Holistic Health Records

Descripción del proyecto

Ayuda a la detección e intervención del cáncer de páncreas mediante inteligencia artificial

El cáncer de páncreas raramente se detecta durante sus fases tempranas, cuando es más curable, principalmente debido a la falta de síntomas. Esto exige el uso de métodos novedosos que respalden la detección temprana, la mitigación de los riesgos y el apoyo a la toma de decisiones hacia intervenciones optimizadas. El proyecto iHELP, financiado con fondos europeos, diseñará un paquete de apoyo a la toma de decisiones que incorpore métodos de identificación y mitigación de riesgos basados en inteligencia artificial para ayudar a luchar contra el cáncer de páncreas. Analizará en detalle los datos históricos e identificará los principales factores de riesgo, al mismo tiempo que aumenta la concienciación y ofrece gestión continua de los riesgos al aprovechar los datos obtenidos mediante varios dispositivos ponibles. El objetivo es ofrecer una evaluación de riesgos casi en tiempo real, para ayudar significativamente en la detección, la prevención y el tratamiento.

Objetivo

The specific focus of iHELP is on early identification and mitigation of the risks associated with Pancreatic Cancer based on the application of advance AI-based learning and decision support techniques on the historic (primary) data of Cancer patients gathered from established data banks and cohorts. This analysis helps to (i) determine key risks associated with Pancreatic Cancer, (ii) develop predictive models for identified risks, and (iii) develop adaptive models for targeted prevention and intervention measures. Based on these developments, the project selects high-risk individuals that are invited to take part in the pilot activities or digital trials. The digital trials are carried out through user-centric mobile and wearable applications that apply proven usability principles to offer more awareness, more engaging experience for health monitoring, risk assessment and personalised decision support. Close collaboration between clinical and AI experts focus on drawing decision support against identified/predicted risks and providing personalised recommendations (e.g. lifestyle changes, behavioural nudges, screening test etc) to the participants in the digital trials. The iHELP (mobile and wearable) technology solutions help in validating iHELP solutions and raising health related awareness at individual level. The (secondary) data gathered through the mobile and wearable applications (concerning life style, behavioural, social interactions and response to targeted prevention and intervention measures) is integrated with primary data in the standardised HHR format – within a big data platform. Frugal AI-based learning techniques are developed to provide near real-time risk assessment based on the integrated and standardised HHR data. iHELP solutions are targeted at multiple stakeholders, including policymakers that will get decision support on the design of new screening programs and new guidelines for bringing improvements in clinical and lifestyle aspects.

Convocatoria de propuestas

H2020-SC1-DTH-2018-2020

Consulte otros proyectos de esta convocatoria

Convocatoria de subcontratación

H2020-SC1-DTH-2020-1

Régimen de financiación

RIA - Research and Innovation action

Coordinador

UNIVERSITY OF PIRAEUS RESEARCH CENTER
Aportación neta de la UEn
€ 424 062,50
Dirección
AL. PAPANASTASIOU 91
185 33 PIRAEUS
Grecia

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Región
Αττική Aττική Πειραιάς
Tipo de actividad
Higher or Secondary Education Establishments
Enlaces
Coste total
€ 424 062,50

Participantes (17)