Brief description
Despite the attention surrounding the recent COVID-19 pandemic, non-communicable diseases (NCDs) are the leading cause of death and healthcare expense. Often such diseases have their origins in unhealthy lifestyles developed in youth.
SmartCHANGE is a Horizon-Europe Research & Innovation project dedicated to the development of powerful AI-enabled long-term risk prediction models for cardiovascular and metabolic disease in young people aged 5–19, an age group where unhealthy lifestyle habits are prevalent. In doing so, SmartCHANGE will make a strong contribution to the UN Sustainable Goal of lifelong Good Health and Well-Being for our citizens.
May 2023 to Apr 2027
Ongoing
Type:
Cloud, Edge, IoT, AI, Data
HEALTHCARE
Website:
https://www.smart-change.eu/
Our role
Effective communication and dissemination are essential in the SmartCHANGE project, which aims to empower young people to build a healthier future by addressing health risks and promoting positive lifestyle changes. Trust-IT, with its extensive experience in healthcare technology projects such as Panacea, is responsible for overseeing the project's events programme, designing and implementing promotion activities, and creating the main website portal that serves as the initiative's flagship online presence and reference point.
Trust-IT's role in SmartCHANGE includes several key activities:
- Developing the project's branding to ensure high visibility, including creating a project logo, flyer, roll-up banner, and other branded materials.
- Coordinating promotional activities across various channels, including regular updates on the SmartCHANGE website and social media platforms, as well as organising webinars, workshops, and healthy lifestyle tours.
- Producing engaging video content to promote the project and its goals.
- Keeping abreast of new trends in healthcare technology helps healthcare organisations and citizens make better-informed decisions about prevention and treatment options.
- Conducting competitor analysis and defining the unique value proposition to position SmartCHANGE effectively in the healthcare market.
- Providing recommendations for AI-based risk prediction and personalised prevention strategies.
In addition, Trust-IT is involved in the SmartCHANGE Proof-of-concept study, which involves recruiting participants from four diverse sites in the Netherlands, Finland, Portugal, and Slovenia. Trust-IT is responsible for designing and implementing recruitment procedures and developing a detailed strategy for each site. The outcomes of the study will be analysed and evaluated, with Trust-IT contributing to the analysis of user experience and usability of the SmartCHANGE applications.
Impact
SmartCHANGE develops an ecosystem to provide tools for improving children's risk prediction of lifetime CVD (cardiovascular disease) and metabolic disease, AI trustworthiness, citizens-health professionals data exchange and interaction, as well as the implementation of recommendations, and training. Thanks to this ecosystem, SmartCHANGE will impact the ability of its stakeholders to share knowledge, taking data-driven, evidence-based, and inclusive decisions that leave no one behind. Through its communication and dissemination efforts, Trust-IT ensures SmartCHANGE contributions to society by raising awareness about the importance of a healthy lifestyle and empowering citizens to better manage their health by changing unhealthy behaviours.
- Economic Impact:
- Reduced costs of medical visits/hospitalisation Maximized long-term health benefits/costs
- Tools & AI models monetisation
- Societal Impact:
- Better citizen – health professionals communication
- Increased awareness via risk prediction tools
- Lifestyle and health literacy enhancement/asses
- Scientific Impact:
- Global recommendations for implementation
- Targeted risk prediction and analysis
- Increased data availability for research
- Effective research, use, re-use, and exploitation
Results
- Explainability of the models and AI predictions
- Privacy-preserving risk prediction
- Trustworthy risk prediction
- Federated learning for data privacy
- Representative data and robust models
- AI bias detection and avoidance
- Visual analytics
- Citizens’ mHealth application
- Health professionals’ web application
- Implementation recommendations
- Family setting feasibility study in Portugal
- Primary school feasibility study in Finland
- Primary healthcare facilities study in The Netherlands
- Community approach feasibility study in Slovenia
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