AI IN HEALTH PREVENTION
Discussion Points ▪ Explored the role of AI in health prevention at both individual and population levels ▪ Discussed the importance of personalisation in health prevention approaches ▪ Examined how AI could help identify at-risk populations and target interventions ▪ Considered the challenges of data quality, privacy, and interoperability ▪ Debated the effectiveness of wearable technology (like Oura rings) for health monitoring ▪ Explored how AI could help identify personal motivators for behaviour change ▪ Discussed the potential for AI to analyse social media data to understand health behaviours Investigate how AI can meet people where they are to tailor health messages ▪ Consider how to make preventative health tools accessible to all populations ▪ Explore ways to use AI to identify what motivates individuals to change behaviour ▪ Look into how AI can help identify high-risk individuals earlier for intervention ▪ Research the return on investment for preventative health interventions Key Actions ▪ Participants shared personal experiences with health monitoring technology ▪ Discussed the challenge of engaging young people (17-24) who prefer in-person interactions ▪ Noted the equity challenges in health technology access ▪ Highlighted the importance of trust and transparency in health data collection ▪ Acknowledged the tension between commercial interests and public health goals ▪ Discussed the Saudi Arabian and Finnish approaches to preventative health Additional Notes ▪
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