A European research and innovation project
INsu-LINE: Advancing Integrated, Data-Driven Care for Chronic Conditions
Type 2 diabetes increases cardiovascular risk up to 4-fold. INsu-LINE uses artificial intelligence to anticipate that risk and protect every patient before complications arise.
INsu-LINE is a research project funded under Italy’s National Recovery and Resilience Plan (PNRR), within the DARE Digital Lifelong Prevention programme. Coordinated by the University of Naples Federico II, the project develops an AI-powered system to stratify cardiovascular risk in type 2 diabetes patients across Italy.
KEY NUMBERS
The Challenge In Numbers
People living with
type 2 diabetes in Italy
Increased cardiovascular risk
Earlier CVD onset vs. general population
Clinical centres across Italy
What INsu-LINE Delivers
01
Interoperable Health and Care Data
INsu-LINE develops a federated and interoperable knowledge base integrating longitudinal health and care data from multiple clinical settings. This approach enables harmonised data analysis while ensuring privacy, security, and compliance with ethical and regulatory requirements.
02
AI-Enabled Risk & Decision Support
The project designs and validates AI-based risk stratification models to support the early identification of cardiovascular complications in people living with chronic conditions. These tools provide actionable insights to healthcare professionals, strengthening evidence-based and personalised clinical decision-making.
03
Integrated and Preventive Care Pathways
INsu-LINE supports the development of integrated and preventive care pathways by translating data-driven insights into coordinated clinical actions. The project fosters collaboration across healthcare professionals, services, and stakeholders to improve continuity, quality, and sustainability of care.
TRANSFORMING INTEGRATED CARE
THROUGH DATA AND AI
Building a Data-Driven Ecosystem for Integrated and Preventive Care
INsu-LINE is a research and innovation initiative aiming to enable integrated and preventive care through interoperable data infrastructures, advanced analytics, and AI-driven decision support tools. The project supports healthcare systems in identifying risk early, coordinating care pathways, and improving long-term outcomes.
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Interoperable Health Data Infrastructure
Development of secure, interoperable data environments enabling the integration of health and care information across settings, supporting continuity of care and advanced analytics.
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AI-Driven Risk Stratification and Predictive Analytics
Application of artificial intelligence models to identify high-risk populations, support clinical decision-making, and enhance early prevention strategies.
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Integrated and Preventive Care Pathways
Design and implementation of coordinated care pathways that promote prevention, multidisciplinary collaboration, and long-term health system sustainability.