Trained SVMs

These SVMs are needed to run 3 out of 4 implementations of neonatal seizure detection algorithms (https://github.com/ktapani/Neonatal_Seizure_Detection). The fullSVM_XXXs are trained on all data in https://zenodo.org/record/1280684#.Wxh3QkiFNaQ, and can be used to detect seizures in new EEG data. The svmXXXs are trained on cross validated data and can be used to reproduce results presented in: K. Tapani, S. Vanhatalo and N. Stevenson, Time-varying EEG correlations improve automated neonatal seizure detection, International Journal of Neural Systems. (accepted for publication)

搜集汇总

背景与挑战

背景概述

该数据集包含训练好的支持向量机（SVM）模型，专门用于新生儿癫痫检测算法的实现。这些模型基于新生儿脑电图（EEG）数据训练，包括用于新EEG数据检测的完整训练模型和用于重现研究结果的交叉验证模型。数据集大小为24.6 GB，主要应用于医疗领域的自动化癫痫检测研究。