Information Methods for Predicting Risk and Outcome of Stroke

  • Wen LiangEmail author
  • Rita KrishnamurthiEmail author
  • Nikola KasabovEmail author
  • Valery FeiginEmail author
Part of the Springer Handbooks book series (SHB)


Stroke is a major cause of disability and mortality in most economically developed countries. It is the second leading cause of death worldwide (after cancer and heart disease) [55.1,2] and a major cause of disability in adults in developed countries [55.3]. Personalized modeling is an emerging effective computational approach, which has been applied to various disciplines, such as in personalized drug design, ecology, business, and crime prevention; it has recently become more prominent in biomedical applications. Biomedical data on stroke risk factors and prognostic data are available in a large volume, but the data are complex and often difficult to apply to a specific person. Individualizing stroke risk prediction and prognosis will allow patients to focus on risk factors specific to them, thereby reducing their stroke risk and managing stroke outcomes more effectively. This chapter reviews various methods–conventional statistical methods and computational intelligent modeling methods for predicting risk and outcome of stroke.


Ischemic Stroke Artificial Neural Network Model Personalized Modeling Spike Neural Network Conventional Statistical Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



artificial neural network


cardiovascular health study


K nearest neighbor


National Institute of Neurological Disorders and Stroke


neural network


straight filament


spiking neural network


spatio-temporal data


World Health Organization


weighted nearest neighbor


weighted distance and weighted variables K nearest neighbor


evolving spiking neural network


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Copyright information

© Springer-Verlag 2014

Authors and Affiliations

  1. 1.School of Computing and Mathematical ScienceAuckland University of TechnologyAucklandNew Zealand
  2. 2.National Institute for Stroke and Applied NeurosciencesAUT UniversityAucklandNew Zealand
  3. 3.KEDRI – Knowledge Engineering and Discovery Research InstituteAuckland University of TechnologyAucklandNew Zealand
  4. 4.National Institute for Stroke and Applied NeurosciencesAUT UniversityNorthcoteNew Zealand

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