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Health research needs more comprehensive accessibility measures: integrating time and transport modes from open data.

Henrikki TenkanenPerttu SaarsalmiOlle JärvMaria SalonenTuuli Toivonen
Published in: International journal of health geographics (2016)
This study demonstrates that time and transport modes are essential components when modeling health-related accessibility in urban environments. Neglecting them from spatial analyses may lead to overly simplified or even erroneous images of the realities of accessibility. Hence, there is a risk that health related planning and decisions based on simplistic accessibility measures might cause unwanted outcomes in terms of inequality among different groups of people.
Keyphrases
  • deep learning
  • minimally invasive
  • optical coherence tomography
  • type diabetes
  • machine learning
  • convolutional neural network
  • artificial intelligence