IDEAS home Printed from https://ideas.repec.org/a/igg/jrqeh0/v6y2017i2p49-69.html
   My bibliography  Save this article

An Artificial Intelligence Approach to Thrombophilia Risk

Author

Listed:
  • João Vilhena

    (Universidade de Évora, Évora, Portugal)

  • Henrique Vicente

    (Universidade de Évora, Évora, Portugal)

  • M. Rosário Martins

    (Universidade de Évora, Évora, Portugal)

  • José Grañeda

    (Hospital do Espírito Santo de Évora, Évora, Portugal)

  • Filomena Caldeira

    (Hospital do Espírito Santo de Évora, Évora, Portugal)

  • Rodrigo Gusmão

    (Hospital do Espírito Santo de Évora, Évora, Portugal)

  • João Neves

    (Drs. Nicolas & Asp, Dubai, UAE)

  • José Neves

    (Universidade do Minho, Braga, Portugal)

Abstract

Thrombophilia stands for a genetic or an acquired tendency to hypercoagulable states, frequently as venous thrombosis. Venous thromboembolism, represented mainly by deep venous thrombosis and pulmonary embolism, is often a chronic illness, associated with high morbidity and mortality. Therefore, it is crucial to identify the cause of the disease, the most appropriate treatment, the length of treatment or prevent a thrombotic recurrence. This work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model has been quite accurate in the assessment of thrombophilia predisposition (accuracy close to 95%). Furthermore, the model classified properly the patients that really presented the pathology, as well as classifying the disease absence (sensitivity and specificity higher than 95%).

Suggested Citation

  • João Vilhena & Henrique Vicente & M. Rosário Martins & José Grañeda & Filomena Caldeira & Rodrigo Gusmão & João Neves & José Neves, 2017. "An Artificial Intelligence Approach to Thrombophilia Risk," International Journal of Reliable and Quality E-Healthcare (IJRQEH), IGI Global, vol. 6(2), pages 49-69, April.
    • Handle: RePEc:igg:jrqeh0:v:6:y:2017:i:2:p:49-69
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJRQEH.2017040105
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:jrqeh0:v:6:y:2017:i:2:p:49-69. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.