Scholarly Research Excellence
@article{(International Science Index):http://waset.org/publications/1901,
  title    = {Predictions Using Data Mining and Case-based Reasoning: A Case Study for Retinopathy},
  author    = {Vimala Balakrishnan and  Mohammad R. Shakouri and  Hooman Hoodeh and  Loo and  Huck-Soo},
  country   = {},
  institution={},
  abstract  = {Diabetes is one of the high prevalence diseases
worldwide with increased number of complications, with retinopathy
as one of the most common one. This paper describes how data
mining and case-based reasoning were integrated to predict
retinopathy prevalence among diabetes patients in Malaysia. The
knowledge base required was built after literature reviews and
interviews with medical experts. A total of 140 diabetes patients- data
were used to train the prediction system. A voting mechanism selects
the best prediction results from the two techniques used. It has been
successfully proven that both data mining and case-based reasoning
can be used for retinopathy prediction with an improved accuracy of
85%.},
    journal   = {International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering},  volume    = {6},
  number    = {3},
  year      = {2012},
  pages     = {55 - 58},
  ee        = {http://waset.org/publications/1901},
  url       = {http://waset.org/Publications?p=63},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 63, 2012},
}