Abstract:Privacy protection, high labeling cost, and the varying characteristics of seizures among patients and at different times are the main obstacles to building seizure detection models. In light of these, we propose a novel Mentor-Student architecture for Patient-Specific seizure detection (MS4PS). It contains a new way of knowledge transferring named mentor-select-for-student, which exploits the knowledge of a Mentor model by using this model to select data for training a Student model, making it possible to avo… Show more
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