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Research Paper | Neuroscience | Volume 6 Issue 6, June 2017 | Pages: 2051 - 2054 | India
Predicting the Outcome of Surgery in Patients with Medically Refractory Temporal Lobe Epilepsy ?Artificial Neural Networks Model
Abstract: BACKGROUND AND AIMS To use an artificial neural networks (ANN) model based entirely on presurgical clinical and investigation variables for predicting postoperative surgical outcome for patients who underwent surgery for medically refractory temporal lobe epilepsy (TLE), and at the same time to compare with binary logistic regression model (BLR) using the Engel outcome. METHODS The subjects included were 115 patients with temporal lobe epilepsy who underwent surgery and had at least 1 year post surgery follow up. Initially 17 presurgical variables were coded on binary scale and depending on p value (
Keywords: Epilepsy Surgery, Prediction, Artificial Neural Networks and Binary logistic regression
How to Cite?: Prof. Dilip Kumar Kulkarni, Dr. S. Sita Jayalakshmi, Dr. Manas K. Panigrahi, "Predicting the Outcome of Surgery in Patients with Medically Refractory Temporal Lobe Epilepsy ?Artificial Neural Networks Model", Volume 6 Issue 6, June 2017, International Journal of Science and Research (IJSR), Pages: 2051-2054, https://www.ijsr.net/getabstract.php?paperid=ART20174767, DOI: https://dx.doi.org/10.21275/ART20174767