• DocumentCode
    3725339
  • Title

    Hybrid Prediction Method for pregnancy data set

  • Author

    Rupali Sawant;Nikhil Gaikwad

  • Author_Institution
    Department of Information Technology, Sardar Patel Institute of Technology, Mumbai, India
  • fYear
    2015
  • Firstpage
    918
  • Lastpage
    920
  • Abstract
    The term Pregnancy is highly risky for the mother and fetus where generally country like India,the population of Pregnant women is more and also where large number of infants born annually with birth defects is more and where their is need of prediction required to see pregnancy is at normal or abnormal in earlier stage so that birth defects can be control. Where prediction cannot based on one method as their many areas of concern so we have to move on Hybrid Prediction Method and on specified data set of age, BMI, vitamin and minerals where we will use Naive Bayes Kernel[5] for predicting pregnancy is normal or not and then Markov Model[6] for decision making for if pregnancy abnormal what tablets should be given of vitamin and mineral[7] for pregnancy to become normal with no harm to infants.
  • Keywords
    "Pregnancy","Minerals","Kernel","Indexes","Markov processes","Predictive models","Pediatrics"
  • Publisher
    ieee
  • Conference_Titel
    Next Generation Computing Technologies (NGCT), 2015 1st International Conference on
  • Type

    conf

  • DOI
    10.1109/NGCT.2015.7375253
  • Filename
    7375253