The Exploratory Research Using BP Neural Network to Analyze the Influencing Factors of Hospitalization Expenses in Acute Appendicitis

  • Jianhui Wu
  • Jie Tang
  • Guoli Wang
  • Sufeng Yin
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 113)


It has no requisition to the distribution of hospitalization expenses using BP neural network, and the network can fit the complex relations between input and output variables. The article establishes the model of BP neural network, and analyzes influencing factors of hospitalization expenses in acute appendicitis. The results display: the first factor influencing hospitalization expenses is the days in hospital. In order to control expenses of acute appendicitis, hospitals should improve the levels of diagnosing and treating, and decurtate days in hospital.


Neural network Hospitalization expenses Acute appendicitis Influencing factors Days in hospital 


  1. 1.
    Zhang H, Tan P (2009) Analysis of hospitalization fee and its influencing factors of 10296 cases with acute appendicitis. Chin Health Econ Mag 23(3):66Google Scholar
  2. 2.
    Wang J, Chen J (2010) Principle and design tips of BP neural network. China J Health Stat 25(5):547–549Google Scholar
  3. 3.
    Zhang W, Zhu L, Wang J (2011) BP neural network based analysis of factors influencing hospitalization expenses in TCM hospitals. Chin J Hosp Adm 21(3):161–165Google Scholar
  4. 4.
    Liao S (2006) Analysis of hospitalization fee and its influencing factors of 1063 cases with acute appendicitis. J Hosp Stat 10(4):223–224Google Scholar
  5. 5.
    Ye X, Lv J, Tan S (2008) Analysis of influencing factors of hospitalization fee of 660 cases with acute appendicitis. J Hosp Stat 14(1):32–33Google Scholar
  6. 6.
    Yang H (2010) Discussion about shorten the average hospitalization days. Mod Hosp 9(2):100–101Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Hebei Province Key Laboratory of Occupational Health and Safety for Coal Industry, Division of Epidemiology and Health Statistics, School of Public HealthHebei United UniversityTang ShanChina

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