• DocumentCode
    2495745
  • Title

    A Novel Data Transformation Method for Serologic Diagnosis of Schistosomiasis Japonica

  • Author

    Tu, X. ; Luo, J. ; Zhou, M. ; Zheng, Y. ; Zhang, Y. ; Xu, J. ; Wu, G. ; Wu, H.

  • Author_Institution
    Dept. of Math. & Comput. Sci., Nanjing Med. Univ., Nanjing, China
  • fYear
    2009
  • fDate
    11-13 June 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Our study established a new serodiagnostic data transformation method of schistosomiasis japonica such that the cut off value based on normal distribution can be used. Sera collected in 2 different Schistosoma japonica (S j) endemic areas were tested by using a S j specific IgG antibody detection kit. The data were assessed by Stata. Results indicated that before the proposed transformation, the specific antibody level of either population was not normally distributed, but after applying the transformation formula, the level of S j egg positive population was transformed to a normal distribution. As Kato Katz stool examination method may miss some infections, the antibody level of the egg negative population was still not normally distributed after the transformation. Based on the theory of normal distribution, a cutoff value was determined by the antibody level of S j egg positive population. We also proposed a new method to determine the cutoff value for serodiagnosis of S j in a population from S j endemic area.
  • Keywords
    biology computing; microorganisms; normal distribution; zoology; S j egg positive population; Schistosomiasis japonica; antibody; data transformation; normal distribution; serologic diagnosis; Computer science; Diseases; Gaussian distribution; Humans; Immune system; Mathematics; Medical diagnostic imaging; Pathogens; Reliability theory; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2901-1
  • Electronic_ISBN
    978-1-4244-2902-8
  • Type

    conf

  • DOI
    10.1109/ICBBE.2009.5162217
  • Filename
    5162217