Deep Learning-Based Assessment of Built Environment From Satellite Images and Cardiometabolic Disease Prevalence.

Journal: JAMA cardiology
PMID: 38691380

Abstract

IMPORTANCE: Built environment plays an important role in development of cardiovascular disease. Large scale, pragmatic evaluation of built environment has been limited owing to scarce data and inconsistent data quality.

Authors

  • Zhuo Chen
    State Key Laboratory Breeding Base of Green Pesticide and Agricultural Bioengineering, Key Laboratory of Green Pesticide and Agricultural Bioengineering, Ministry of Education, Guizhou University, Huaxi District, Guiyang 550025, China. Electronic address: gychenzhuo@aliyun.com.
  • Jean-Eudes Dazard
    Harrington Heart and Vascular Institute, University Hospitals, 11100 Euclid Ave, Cleveland, OH 44106, USA.
  • Yassin Khalifa
    Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA.
  • Issam Motairek
    Harrington Heart and Vascular Institute, University Hospitals, 11100 Euclid Ave, Cleveland, OH 44106, USA.
  • Catherine Kreatsoulas
    Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts.
  • Sanjay Rajagopalan
    Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.
  • Sadeer Al-Kindi
    Division of Cardiology, Department of Medicine (S.A.-K., F.N., G.F.A., M.A.C., D.I.S., M.S.A., J.A.M., S.G.T.), Case Western Reserve University, Harrington Heart and Vascular Institute, and University Hospitals Cleveland Medical Center, OH.

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