Using machine learning to examine associations between the built environment and physical function: A feasibility study

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Rachele, Jerome ORCID: 0000-0002-5101-4010 (external link), Wang, Jingcheng, Wijnands, Jasper S, Zhao, Haifeng, Bentley, Rebecca and Stevenson, Mark (2021) Using machine learning to examine associations between the built environment and physical function: A feasibility study. Health and Place, 70. ISSN 1353-8292

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/42432
DOI 10.1016/j.healthplace.2021.102601 (external link)
Official URL https://www.sciencedirect.com/science/article/abs/... (external link)
Funders http://purl.org/au-research/grants/nhmrc/497236 (external link), http://purl.org/au-research/grants/nhmrc/1047453 (external link), http://purl.org/au-research/grants/nhmrc/339718 (external link)
Subjects Current > FOR (2020) Classification > 3304 Urban and regional planning
Current > FOR (2020) Classification > 4206 Public health
Current > Division/Research > Institute for Health and Sport
Current > Division/Research > College of Health and Biomedicine
Keywords deep learning; neighbourhood design; urban design; aerial images; physical activity; health-enhancing behaviours
Citations in Scopus 5 - View on Scopus (external link)
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