TY  - CONF
  - Ahmad, A., Temko, A., Marnane, W.P., Boylan, G. and Lightbody, G.
  - IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP -2014
  - Grading Brain Injury in Neonatal EEG using SVM and Supervector Kernal
  - 2014
  - May
  - Published
  - 1
  - ()
  - 5894
  - 5898
  - Florence, Italy
  - 04-MAY-15
  - 09-MAY-15
  - Brain injury at the time of birth could lead to severe neurological dysfunction at an older age. Grading the brain injury in the early hours after birth could help doctors determine a prompt and reliable treatment. This work presents an automated neonatal EEG grading system based on a crossdisciplinary method of using Support Vector Machine and supervectors, initially developed for speaker identification. The EEG is classified into one of the four grades of neonatal brain injury. The preliminary results show promising performance and are an improvement on the previously published results.
  - 10.1109/ICASSP.2014.6854734
  - Science Foundation Ireland
  - 12/RC/2272
DA  - 2014/05
ER  - 

@inproceedings{V286677610,
   = {Ahmad, A., Temko, A., Marnane, W.P., Boylan, G. and Lightbody, G.},
   = {IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP -2014},
   = {{Grading Brain Injury in Neonatal EEG using SVM and Supervector Kernal}},
   = {2014},
   = {May},
   = {Published},
   = {1},
   = {()},
  pages = {5894--5898},
   = {Florence, Italy},
  month = {May},
   = {09-MAY-15},
   = {{Brain injury at the time of birth could lead to severe neurological dysfunction at an older age. Grading the brain injury in the early hours after birth could help doctors determine a prompt and reliable treatment. This work presents an automated neonatal EEG grading system based on a crossdisciplinary method of using Support Vector Machine and supervectors, initially developed for speaker identification. The EEG is classified into one of the four grades of neonatal brain injury. The preliminary results show promising performance and are an improvement on the previously published results.}},
   = {10.1109/ICASSP.2014.6854734},
   = {Science Foundation Ireland},
   = {12/RC/2272},
  source = {IRIS}
}