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Journal of Medical Systems

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01.08.2010 | Original Paper

Can Neural Network Able to Estimate the Prognosis of Epilepsy Patients Accorrding to Risk Factors?

verfasst von: Kezban Aslan, Hacer Bozdemir, Cenk Sahin, S. Noyan Ogulata

Erschienen in: Journal of Medical Systems | Ausgabe 4/2010

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Abstract

The aim of this study is to evaluate the underlying etiologic factors of epilepsy patients and to predict the prognosis of these patients by using a Multi-Layer Perceptron Neural Network (MLPNN) according to risk factors. 758 patients with epilepsy diagnosis are included in this study. The MLPNNs were trained by the parameters of demographic properties of the patients and risk factors of the disease. The results show that the most crucial risk factor of the epilepsy patients was constituted by the febrile convulsion (21.9%), the kinship of parents (22.3%), the history of epileptic relatives (21.6%) and the history of head injury (18.6%). We had 91.1 % correct prediction rate for detection of the prognosis by using the MLPNN algorithm. The results indicate that the correct prediction rate of prognosis of the MLPNN model for epilepsy diseases is found satisfactory.

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Titel: Can Neural Network Able to Estimate the Prognosis of Epilepsy Patients Accorrding to Risk Factors?
verfasst von: Kezban Aslan
Hacer Bozdemir
Cenk Sahin
S. Noyan Ogulata
Publikationsdatum: 01.08.2010
Verlag: Springer US
Erschienen in: Journal of Medical Systems / Ausgabe 4/2010
Print ISSN: 0148-5598
Elektronische ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-009-9267-8

Springer Medizin

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