Why the study?
Current tools for identifying individuals at high risk of non-communicable chronic diseases focus mainly on adults, missing early detection and intervention opportunities during childhood and adolescence.
Does the SmartCHANGE AI-driven decision-support tool improve risk identification and behavior change for NCD prevention in children and youth?
Does the SmartCHANGE AI-driven decision-support tool improve risk identification and behavior change for NCD prevention in children and youth?
The SmartCHANGE project outlines a methodology for developing trustworthy, AI-driven decision-support tools using federated learning and explainable AI to identify and mitigate long-term non-communicable disease risks in children and youth.
Answers are grounded in this paper and cite their sources.
Methodology for trustworthy AI NCD tools in youth is now defined; prospective trials needed before clinical adoption.
The SmartCHANGE project, a Horizon-Europe Research & Innovation project that has been ongoing since May 2023 and is scheduled to conclude in April 2027, aims to develop AI-driven decision-support tools to identify and reduce the long-term risk of non-communicable chronic diseases (NCDs) in children and youth. NCDs have become a significant public health burden in developed countries, with common risk factors including obesity, low physical fitness, and unhealthy lifestyle habits. Childhood and adolescence are critical periods for establishing healthy habits, and early intervention can prevent or delay the onset of NCDs later in life. However, current tools for identifying high-risk individuals mainly focus on adults, leading to missed opportunities for early detection. The SmartCHANGE project aims to address this gap by creating trustworthy AI tools that accurately assess risk factors in children and youth and promote optimised strategies for risk reduction. The paper outlines the plan for the project from the project’s proposed methodologies, including dataset utilisation, data cleaning, risk prediction models (basic and complex), and the implementation of federated learning. Additionally, it discusses user experience aspects such as participatory design, suggested applications, and the evaluation of project outcomes.
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Reščič et al. (2023) studied this question.
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