International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Open Access | Double Blind Reviewed

ISSN: 2319-7064

Downloads: 100

Research Paper | Neuroscience | India | Volume 6 Issue 6, June 2017

Predicting the Outcome of Surgery in Patients with Medically Refractory Temporal Lobe Epilepsy ?Artificial Neural Networks Model

Prof. Dilip Kumar Kulkarni | Dr. S. Sita Jayalakshmi | Dr. Manas K. Panigrahi

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 (<0.05) with logistic regression forward selection 3 predictors were selected namely imaging (MRI), partial seizures with secondary generalization and seizure frequency for developing the models. Outcome was assessed using ANN and BLR according to Engel outcome classifications on binary scale. RESULTS The 115 datasets of the patients were used for classification by BLR and ANN methods for predicting the Engel outcome. BLR model sensitivity 80 %, specificity 85 % and that of ANN Sensitivity 80 % specificity 85 %, however the ROC area under curve for BLR is 0.703 and ANN is 0.732. The ANN model the ROC area under curve is higher compared to BLR model. CONCLUSIONS Using artificial neural networks, prediction models were developed to predict the outcome of surgery in patients with refractory temporal lobe epilepsy by using simple pre-operative clinical and investigation parameters. The ANN classifier performed better than BLR classifier.

Keywords: Epilepsy Surgery, Prediction, Artificial Neural Networks and Binary logistic regression

Edition: Volume 6 Issue 6, June 2017,

Pages: 2051 - 2054

How to Download this Article?

You Need to Register Your Email Address Before You Can Download the Article PDF

How to Cite this Article?

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", International Journal of Science and Research (IJSR), Volume 6 Issue 6, June 2017, pp. 2051-2054,

Similar Articles with Keyword 'Epilepsy'

Downloads: 0

Survey Paper, Neuroscience, India, Volume 10 Issue 9, September 2021

Pages: 380 - 383

Social Prejudice against Epilepsy, due to Lack of Awareness among Students - A Teenager's Perspective

Archisha Bansal

Share this Article

Downloads: 94 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

Research Paper, Neuroscience, India, Volume 9 Issue 7, July 2020

Pages: 341 - 345

An Assessment of 24-Hour Ambulatory Electroencephalography [EEG] Monitoring in New Onset Idiopathic Generalized Epilepsy [IGE]

Dr. Dinesh Khandelwal [2] | Dr. Chandrajeet Singh Ranawat | Dr. Divya Goel | Dr. Manu L S

Share this Article