<ul><li>Air pollution is a significant threat to public health, leading to respiratory and cardiovascular diseases, exacerbated by climate change-induced extreme weather events.</li><li>Advancements in personal sensing technology and AI capabilities enable the prediction of individual health responses to pollution exposure.</li><li>A novel workflow integrates physiological data from wearable fitness devices with real-time environmental exposures to monitor and predict health outcomes.</li><li>An Adversarial Autoencoder neural network is used to accurately predict individual health responses to pollution exposure, showcasing the adaptability of the approach to real-world data.</li></ul>

An AI-driven framework for the prediction of personalised health response to air pollution

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