首页> 外文会议>IASTED(International Association of Science and Technology for Development) International Conference on Modelling, Simulation, and Optimization >VIDEO EEG EXPERT SYSTEM: SOFTWARE TO COMPUTE SEIZURE FOCUS LATERALIZATION AND LOCALIZATION PRIOR TO EPILEPSY SURGERY
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VIDEO EEG EXPERT SYSTEM: SOFTWARE TO COMPUTE SEIZURE FOCUS LATERALIZATION AND LOCALIZATION PRIOR TO EPILEPSY SURGERY

机译:视频EEG专家系统:在癫痫手术前计算癫痫发作聚焦横向化和定位的软件

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OBJECTIVE: To develop the Video EEG Expert System (VES), a program to analyze patient data with the goal of finding anatomic seizure focus in the context of epilepsy pre-surgical evaluation. BACKGROUND: Numerous systems have been created to analyze electroencephalogram (EEG) data with the goal of searching for epileptiform discharges. Literature review does not reveal software dedicated to evaluation of data for a patient under consideration for temporal lobectomy surgery. METHODS: Patient data included MRI, PET, SPECT, and video EEG. The system is in Lisp and a logic programming module, Prolisp, that supports hypothesis-driven rules. Benchmark files (controls) and corresponding anatomic localization hypothesis trees were created. 23 experimental files were used to test correctness in localizing seizure focus. The principle developer was blind to these files. RESULTS: The system selected the correct localization for 100% of benchmark files. For the experimental files, the correct localization was selected in 78%, first place ties were computed in 13%, and incorrect localizations were found in 9%. Analysis of incorrect results yielded minor software problems and some incomplete knowledge concerning temporal lobe localization. CONCLUSIONS: VES performed well at identifying seizure focus. The tools developed for VES, especially Prolisp, should serve future neurological expert system development.
机译:目的:开发视频EEG专家系统(VES),该计划分析患者数据,目的是在癫痫前手术评估的背景下发现解剖学癫痫发作。背景:已经创建了许多系统以分析脑电图(EEG)数据,其目的是寻找癫痫型排放。文献综述没有透露致力于评估颞叶术手术的患者数据的软件。方法:患者数据包括MRI,PET,SPECT和视频EEG。该系统位于LISP和逻辑编程模块中,ProMISP支持假设驱动的规则。建立基准文件(控件)和相应的解剖定位假设树。 23实验文件用于测试本地化癫痫发作焦点的正确性。原则开发人员对这些文件盲目。结果:系统为100%的基准文件选择了正确的本地化。对于实验文件,在78%中选择了正确的本地化,首先将第一个地点以13%计算,并在9%中发现了不正确的本地化。不正确的结果分析产生了次要的软件问题和关于时间叶本地化的一些不完整知识。结论:ves在识别癫痫发作焦点时表现良好。为VES,尤其是ProMISP开发的工具应提供未来的神经系统专家系统开发。

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