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AuthorQidwai, U.
AuthorShamim, S.
AuthorEnam, A.
Available date2015-12-15T06:52:44Z
Publication Date2010-11
Publication NameApplied Artificial Intelligence
CitationQidwai, U., Shamim, S., Enam, A. Fuzzy prediction for failed back surgery syndrome. (2010) Applied Artificial Intelligence, 24 (10), pp. 881-895.
AbstractIn this article a new strategy is presented that can be used by neurophysicians, neurosurgeons, and orthopedic surgeons to predict patients' health after an operative procedure on the vertebral column just by analyzing the preoperative patient data. Usually, this is done based on the linguistic or heuristic variables related to patient's data, such as marital status, occupation, and so on. There are some numeric variables also involved in the analysis, such as the body mass index, age, and duration of symptoms. Standard Fuzzy Inference System has been developed around mapping the physicians' heuristics, and accordingly the membership degrees and rules have been developed. The results have shown 88% correct prediction on a patient population of 501. Emphasis has been given to overestimate the risk in patients, which is a normal practice in clinical standards for benign diseases. The system is expected to assist medical professionals in making better decisions in terms of posture management, life-style, and pain management postoperatively to prevent the back surgery from failing.
PublisherTaylor and Francis Ltd.
Health risks
Hospital data processing
TitleFuzzy prediction for failed back surgery syndrome
Issue Number10
Volume Number24

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