IDEAS home Printed from https://ideas.repec.org/h/spr/spochp/978-0-387-69319-4_13.html
   My bibliography  Save this book chapter

Diagnosis of Alport Syndrome by Pattern Recognition Techniques

In: Data Mining in Biomedicine

Author

Listed:
  • Giacomo Patrizi

    (Università di Roma “La Sapienza”)

  • Gabriella Addonisio

    (Università di Roma “La Sapienza”)

  • Costas Giannakakis

    (Università di Roma “La Sapienza”)

  • Andrea Onetti Muda

    (Università di Roma “La Sapienza”)

  • Gregorio Patrizi

    (Università di Roma “La Sapienza”)

  • Tullio Faraggiana

    (Università di Roma “La Sapienza”)

Abstract

Alport syndrome is a genetic multi-organ disorder, primarily linked with the X-Chromosome, although autosomal forms have been reported. Ultra-structural observations in some cases indicate highly characteristic lesions and mutations in certain genes. Thus the symptomatology of the syndrome is complex and diverse. The aim of this chapter is to present a pattern recognition algorithm to diagnose with high precision patients who may be subject to Alport syndrome. Images of the epidermal basement membrane are studied and a rule to classify them precisely is presented. Theoretical and experimental results are given regarding the possibility of solving this problem.

Suggested Citation

  • Giacomo Patrizi & Gabriella Addonisio & Costas Giannakakis & Andrea Onetti Muda & Gregorio Patrizi & Tullio Faraggiana, 2007. "Diagnosis of Alport Syndrome by Pattern Recognition Techniques," Springer Optimization and Its Applications, in: Panos M. Pardalos & Vladimir L. Boginski & Alkis Vazacopoulos (ed.), Data Mining in Biomedicine, pages 209-230, Springer.
    • Handle: RePEc:spr:spochp:978-0-387-69319-4_13
    DOI: 10.1007/978-0-387-69319-4_13
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:spochp:978-0-387-69319-4_13. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.