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Bag of Patterns for Nearest Neighbour Neonatal EEG Recall

机译:最近的新生儿脑电图召回模式袋

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摘要

Clinical neurophysiologists often find it difficult to recall rare EEG patterns despite the fact that this information could be diagnostic and help with treatment intervention. Traditional search methods may take time to retrieve the archived EEGs that could provide the meaning or cause of the specific pattern, which is undesirable as time can be critical for sick neonates. If neurophysiologists had the ability to quickly recall similar patterns, the prior occurrence of the pattern may help make an earlier diagnosis. This paper presents a system that may be used to assist a clinical neurophysiologist in the recall of neonatal EEG patterns. This paper compares two brute force approaches for the task of neonatal EEG recall and looks at the performance accuracy, speed and memory requirements. This system was tested on six different neonatal EEG pattern types with 430 events in total and the results are presented in this paper.
机译:尽管该信息可以诊断并有助于治疗干预,但临床神经生理学家经常发现很难回忆起罕见的脑电图模式。传统的搜索方法可能会花费一些时间来检索可能提供特定模式的含义或原因的存档EEG,这是不希望的,因为时间对于生病的新生儿可能至关重要。如果神经生理学家具有快速回忆起类似模式的能力,则该模式的先前发生可能有助于做出更早的诊断。本文介绍了可用于协助临床神经生理学家回忆新生儿脑电图模式的系统。本文比较了两种用于新生儿脑电图检查的蛮力方法,并研究了其性能准确性,速度和记忆要求。该系统在总共430个事件的六种不同的新生儿EEG模式类型上进行了测试,结果在本文中进行了介绍。

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