| Title: | Built environment and health in the UK Biobank: exploring the complex relationship using machine learning approaches |
| Lead Institution: | University of Oxford |
| Principal investigator: | Professor Kazem Rahimi |
Application 43748
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About
This proposed research forms part of a collaborative project led by an interdisciplinary team of researchers with expertise in epidemiology, clinical medicine, machine learning and geospatial information science. We plan to explore how environmental factors, including, but not limited to, physical structures surrounding individuals may influence health and various disease conditions. The UK Biobank collects information about the built environment of the study participants, and we aim to harness the availability of such data resource to examine differences in built environment across the country, and how these differences show similar (or different) patterns of associations with health status, occurrence of diseases, or clustering of disease conditions, across these areas. We will use a range of data science and machine learning approaches to extract, infer, and validate knowledge derived from analysing the data. By analysing the complexity of the relation between built environment and health, we hope to evaluate how well these environmental factors predict various disease conditions as individual factors or as clusters of these factors.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 11154 | Road Traffic Noise and Incidence of Primary Hypertension A Prospective Analysis in UK Biobank | Jing Huang (+6) | 2023 | JACC Advances |
Enabling scientific discoveries that improve human health