Patient-specific seizure onset detection

By Ali H. Shoeb, H. Edwards, Jack Connolly, B. Bourgeois, T. Treves, John V. Guttag. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004

303 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Cognitive Neuroscience, Pulmonary and Respiratory Medicine

View Paper: https://www.semanticscholar.org/paper/e7fac8c1ecebb217c5159b01e39179efe14dca4e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cardiology and Cardiovascular Medicine

1. Ali H. Shoeb

In Cognitive Neuroscience

1. Ali H. Shoeb
2. John V. Guttag

In Pulmonary and Respiratory Medicine

1. Ali H. Shoeb

Citations in the corpus

• Application of Machine Learning To Epileptic Seizure Detection (2010, methodology): “Previous patient-specific algorithms (Qu & Gotman, 1997; Shoeb et al., 2004; Haas et al., 2007) classified temporal, spectral, and spatial features separately, and required an individual skilled in interpreting the brain's electrical activity to specify how such features should be combined.”
• Application of machine learning to epileptic seizure onset detection and treatment (2009, methodology): “We showed in [55, 56] that these values, after adjusting for SVM software package differences, work well on an independent data set consisting of 139 seizures and 49 hours of non-seizure EEG recorded from 36 pediatric epilepsy patients.”