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Epileptic seizure detection has gained increasing attention in clinical therapy. Scalp electroencephalogram (EEG) analysis is a common way to capture brain abnormality for seizure onset detection. This paper presents a novel context-learning based approach using multi-feature fusion to compensate for incomplete description of single feature in epileptic EEG signals. First, EEG scalogram sequence is...
Time series data mining has gained increasing attention in health domain. Recently, researchers attempt to employ Natural Language Processing (NLP) to health data mining, in order to learn proper representations of discrete medical concepts from Electronic Health Records (EHRs). However, existing models do not take continuous physiological records into account, which are naturally existed in EHRs...
Along with the rapid development of communication network construction, the operation energy consumption grows significantly in recent years, and the expensive electricity cost is hard to be ignored. Therefore, it is necessary to develop an operation energy anomaly detection mechanism to enhance the control ability of electricity cost. According to the practical distribution and data characteristic...
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