• DocumentCode
    2818212
  • Title

    Study on the causes of hypertension with improved BP neural network

  • Author

    Dong, Xiuying ; Ping, Wang

  • Author_Institution
    Electr. & Inf. Coll., Xihua Univ., Chengdu, China
  • Volume
    1
  • fYear
    2010
  • fDate
    17-18 April 2010
  • Firstpage
    21
  • Lastpage
    24
  • Abstract
    An improved neural network based on L-M (Levenberg-Marquard) algorithm neural network has been applied to the model for the analysis of factors on Hypertension. It can remedy the shortcoming of the slow convergence rate of traditional BP algorithm neural network. This model can determine which factors are the main reasons for high blood pressure. We have adopted the lattice fuzzy close-degree assessment and expert scoring method which quantified the various data of the factors on high blood pressure. We used the matlab to program and simulate. The results showed that: the improved BP neural network, can determine the main factors which causing the high blood pressure correctly, the error between the Predictive value and the actual value is very small. it reached the desired goal.
  • Keywords
    backpropagation; health care; medical computing; neural nets; BP neural network; L-M algorithm; expert scoring method; high blood pressure; hypertension; lattice fuzzy close degree assessment; predictive value; Algorithm design and analysis; Blood pressure; Convergence; Ecosystems; Educational institutions; Hypertension; Information analysis; Mathematical model; Neural networks; Neurons; BP neural network; Close-degree grid; Hypertension; L-M algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Health Networking, Digital Ecosystems and Technologies (EDT), 2010 International Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4244-5514-0
  • Type

    conf

  • DOI
    10.1109/EDT.2010.5496600
  • Filename
    5496600