• DocumentCode
    2044800
  • Title

    Failed Back Surgery Syndrome (FBSS) Prediction using Fuzzy Inference System (FIS)

  • Author

    Qidwai, Uvais ; Shamim, M. Shahzad ; Raquib, Farhana ; Enam, Ather

  • Author_Institution
    Comput. Sci. & Eng. Dept., Qatar Univ., Qatar
  • fYear
    2007
  • fDate
    24-27 Nov. 2007
  • Firstpage
    880
  • Lastpage
    883
  • Abstract
    In this paper a fuzzy inference system (FIS) is presented to predict the level of risk for a class of patients to be needing a repeated surgery for the herniated lumber disc (or more commonly known as slipped disc). The FIS is based upon a clinical study that was conducted by a number of doctors at Aga Khan University Hospital in Pakistan with the objective that certain clinical measures can be used from the beginning to assist the physician in making a better risk estimate for the patient at hand. As such, over 90 clinical markers were collected through patients´ surveys over a period of 5 years (2000-2004). The presented study utilizes a subset of 16 markers and has recommendation for 7 of these markers for a reasonably accurate risk prediction. A set of 11 rules has been established that constitute the mapped understanding from the physicians´ heuristics. Such a system will be a very helpful tool for medical professionals for making quick risk assessment for a patient and will enable them to more accurately define the treatment for the same.
  • Keywords
    bone; fuzzy reasoning; medical computing; medical disorders; orthopaedics; risk analysis; surgery; failed back surgery syndrome prediction; fuzzy inference system; herniated lumber disc surgery; medical disorder; medical professional; patient treatment; risk assessment; Back; Fuzzy systems; Hospitals; Leg; Medical treatment; Pain; Signal processing; Spine; Surgery; Surges;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications, 2007. ICSPC 2007. IEEE International Conference on
  • Conference_Location
    Dubai
  • Print_ISBN
    978-1-4244-1235-8
  • Electronic_ISBN
    978-1-4244-1236-5
  • Type

    conf

  • DOI
    10.1109/ICSPC.2007.4728460
  • Filename
    4728460