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- W2158363422 abstract "When dealing with seizure detection/prediction problems, there are three main performance metrics that must be optimized: false positive rate, false negative rate, detection delay or, if the problem is seizure prediction, it is desirable to obtain the greatest prediction time achievable. Tuning specific extracted features to individual patients can lead to improved results. The processing window length is also an important parameter whose optimization may significantly affect performance. In this study we propose an approach for selecting the window length for the particular detection/prediction problem. This approach is applicable to other feature parameters suitable for tuning or optimization." @default.
- W2158363422 created "2016-06-24" @default.
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- W2158363422 date "2005-08-25" @default.
- W2158363422 modified "2023-09-24" @default.
- W2158363422 title "Feature parameter optimization for seizure detection/prediction" @default.
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- W2158363422 doi "https://doi.org/10.1109/iembs.2001.1020546" @default.
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