arXiv Machine Learning July 21, 2026 By Maede Azani Hassan Abadi, Shouyi Wang

Interpretable Machine Learning for Air Pollution and Respiratory Health Prediction: A Socioeconomic Subgroup Analysis

Read the original on arXiv Machine Learning →

arXiv:2607. 17024v1 Announce Type: new Abstract: Air pollution and climate-related stressors are increasingly important concerns for respiratory health, especially in settings with unequal environmental exposure and healthcare capacity.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

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arXiv Machine Learning

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AI for Social Good: An Investigation of the Causal Relationship Between Environmental Regulations and Their Effects on Air Pollution in London, UK

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Environmental Drivers of Respiratory Disease: A District Level Analysis

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By Rahim Iqbal, Asfi Ahamed, Izzath Nisfer, Shazan Shaheed, Muhammadu Ilham, Nathali Athukorala, Madara Mendis, Nisansa de Silva, Sandareka Wickramanayake

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Learning to model pediatric asthma exacerbation from multiple risk factors: a case study in coastal Virginia

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