Researchers say that using Google Street View can help provide an overview of physical environmental risk factors in the built and natural environments that could help not only in understanding risk factors in these environments, but ultimately help towards building or adapting towns and cities to make them healthier places to live.
The study was led by Prof. Sadeer Al-Kindi and Prof. Sanjay Rajagopalan from University Hospitals Harrington Heart & Vascular Institute and Case Western Reserve University, Ohio, USA, and Dr. Zhuo Chen, a post-doctoral fellow in Prof. Rajagopalan's laboratory.
Prof. Rajagopalan said: "We have always been interested in how the environment, both the built and natural environment, influences cardiovascular disease. Here in America, they say that the zip code is a better predictor of heart disease than even personal measures of health. However, to investigate how the environment influences large populations in multiple cities is no mean task. Hence, we used machine vision-based approaches to assess the links between the built environment and coronary heart disease prevalence in US cities."
The study included more than half a million Google Street View images of Detroit, Michigan; Kansas City, Missouri; Cleveland, Ohio; Brownsville, Texas; Fremont, California; Bellevue, Washington State; and Denver, Colorado. Researchers also collected data on rates of coronary heart disease according to 'census tracts'. These are areas smaller than a US zip code that are home to an average of 4,000 people. The researchers used an approach called a convolutional neural network; a type of artificial intelligence that can recognise and analyse patterns in images to make predictions.
sources-science daily
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