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, 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 |
| Official URL | https://www.sciencedirect.com/science/article/abs/... |
| Funders | http://purl.org/au-research/grants/nhmrc/497236, http://purl.org/au-research/grants/nhmrc/1047453, http://purl.org/au-research/grants/nhmrc/339718 |
| 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 |
| Download/View statistics | View download statistics for this item |
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