Abstract
Within the EU-funded Pulse project, we are implementing a data analytic platform designed to provide public health decision makers with advanced approaches to jointly analyze maps and geospatial information with health care data and air pollution measurements. In this paper we describe a component of such platform, designed to couple deep learning analysis of geospatial images of cities and some healthcare and behavioral indexes collected by the 500 cities US project, showing that, in New York City, urban landscape significantly correlates with the access to healthcare services.
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Bellazzi, R., Caldarone, A. A., Pala, D., Franzini, M., Malovini, A., Larizza, C., & Casella, V. (2019). Transfer Learning for Urban Landscape Clustering and Correlation with Health Indexes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11862 LNCS, pp. 143–153). Springer. https://doi.org/10.1007/978-3-030-32785-9_13
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