LATE-AYA
Personalized monitoring and support digital platform for young cancer survivors
The project focuses on improving the understanding and management of long-term effects (late effects) in adolescents and young adults (AYA) who have survived cancer.
Detailed project description
The main objectives of the project are:
- the development of a digital phenotyping platform that integrates big data and artificial intelligence for personalized patient monitoring,
- the creation of a multi-factor psychosocial intervention designer that supports patients in coping with the long-term effects of the disease,
- the implementation of an adaptive monitoring system involving multiple stakeholders (physicians, caregivers, social services), ensuring continuous support after the end of treatment,
- the creation of a living lab environment for testing and validating innovative care solutions
The project is aligned with the European Health Data Space (EHDS) guidelines, ensuring data security and interoperability in large-scale health studies.
Type and scope of work provided
The project is divided into individual work packages (WPs), each of which covers specific research and technological activities.
- Coordination and management (WP1): ensuring the proper administrative functioning of the project, compliance with funding rules, and risk assessment.
- Digital phenotyping and data analysis (WP3): development of AI models for analyzing patient data from multiple sources (medical records, wearable devices, lifestyle data).
- Psychosocial intervention designer (WP4): development of personalized psychological interventions through digital tools and implementation of an AI-based chatbot for patient interaction and mental health support.
- Adaptive monitoring system (WP5): creation of a dashboard for collaboration between physicians, social workers, and caregivers, as well as enabling remote real-time monitoring of patient condition.
- Big data and AI for impact prediction (WP7): development of machine learning models to predict complications appearing at later stages, using biometric, genetic, and behavioral data.
- Clinical studies and validation (WP8): implementation of large-scale clinical trials in European healthcare institutions and evaluation of the effectiveness of the solutions under real-world conditions.
- Impact assessment and dissemination (WP9 & WP10): evaluation of the social and economic impact and dissemination of results through scientific publications, conferences, and policy recommendations.
The project represents an important step towards personalized medicine using artificial intelligence, improving the quality of life of cancer survivors through data-driven healthcare solutions.
Ημερομηνία:
June 2025
