Objectives and Key Results

Accurate Risk Prediction Models: Develop precise AI-driven models for forecasting the lifetime risk of non-communicable chronic diseases (NCDs) like cardiovascular and metabolic diseases among children and youth. Utilize advanced machine learning techniques, incorporating diverse variables such as behavior, fitness, and NCD biomarkers, to enhance accuracy and adaptability.

Trustworthy AI Tools: Create robust risk-prediction models and AI tools that prioritize data privacy through federated learning, data accuracy through adaptive learning, and explainability via visual analytics. These tools will offer transparent insights into predictions and risk factors, instilling user trust and understanding.

User-Centric Health Enhancement Tools and Stakeholder Engagement: Develop user-friendly tools for healthcare professionals and citizens, enabling visualization of predicted outcomes based on current and modified lifestyles. These tools will provide personalized risk-lowering strategies, empowering users to make informed decisions about their health habits. Engage health professionals, educators, children, and families in participatory design to co-create risk-prediction models, explanations, and tools, harnessing diverse insights to effectively address users' needs.

Promoting Healthy Lives: Disseminate the SmartCHANGE project's findings and tools, collaborating with institutions to integrate them into healthcare systems. Work towards raising awareness among healthcare professionals, families, and the broader public about the significance of healthy lifestyle choices and the potential for positive change. By providing accessible tools and actionable insights, the project aims to promote healthier lives among children and youth.