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

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contributor.author Qidwai, Uvais en_US
contributor.author Shamim, Shahzad en_US
contributor.author Raquib, Farhana en_US
contributor.author Enam, Ather en_US
date.accessioned 2009-12-29T10:29:59Z en_US
date.available 2009-12-29T10:29:59Z en_US
date.issued 2007-11-24 en_US
identifier.citation Qidwai, U.; Shamim, M.S.; Raquib, F.; Enam, A., "Failed Back Surgery Syndrome (FBSS) Prediction using Fuzzy Inference System (FIS)," Signal Processing and Communications, 2007. ICSPC 2007. IEEE International Conference on , vol., no., pp.880-883, 24-27 Nov. 2007 en_US
identifier.uri http://dx.doi.org/10.1109/ICSPC.2007.4728460 en_US
identifier.uri http://hdl.handle.net/10576/10567 en_US
description.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. en_US
language.iso en en_US
publisher IEEE en
subject FBSS en_US
subject Fuzzy Inference System en_US
subject Fuzzy en_US
subject Inference System en_US
title Failed Back Surgery Syndrome (FBSS) Prediction using Fuzzy Inference System (FIS) en_US
type Article en_US


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