Predicting Lung Disease Severity via Image-Based AQI Analysis using Deep Learning Techniques

arXiv:2405.03981v1 Announce Type: cross
Abstract: Air pollution is a significant health concern worldwide, contributing to various respiratory diseases. Advances in air quality mapping, driven by the emergence of smart cities and the proliferation of Internet-of-Things sensor devices, have led to an increase in available data, fueling momentum in air pollution forecasting. The objective of this study is to devise an integrated approach for predicting air quality using image data and subsequently assessing lung disease severity based on Air Quality Index …

abstract advances air pollution air quality analysis arxiv cities cs.cv cs.lg data deep learning deep learning techniques devices disease diseases emergence health image internet mapping pollution quality sensor smart smart cities type via