Computer-aided decision-making for epilepsy and sleep diagnostics.

L Korpinen
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Abstract

The main objective of the study was first to develop two prototypes of decision support systems for epilepsy and sleep disorder diagnostics. The second goal was to examine medical decision-making with the help of these program examples and further to assess what requirements should be set to decision support systems for them to find their place in clinical work. Requirements were first defined for the systems to be developed. The requirements were, for the most part, successfully taken into consideration during the development process. Epilepsy Expert, a decision support system based on the International Classification of Epilepsies and Epileptic Syndromes (51) was then developed. An epilepsy expert was in a central role in the development work due to the nature of the classification. For sleep disorders Sleep Expert, a decision support system, was developed based on the International Classification of Sleep Disorders (52). In the developing of the system the role of experts in sleep disorders was minor as the international classification provided a good foundation for program knowledge. The knowledge of the programs was validated as follows. First, three experts were requested to provide 10 case descriptions, and then they made diagnoses of their colleagues' patients. On the basis of these diagnoses a majority agreement, 'the right diagnosis', was reached. From the same epilepsy cases the author made diagnoses with the aid of the decision tree of Epilepsy Expert. Two other physicians, who were not experts in sleep disorders, made diagnoses for sleep disorders using Sleep Expert. In the validation Epilepsy Expert proved partly incomplete, which was due in part to the weakness of the international classification. However, the section of the program whose diagnostics was based on clinical findings only was as good as the experts. In the validation of Sleep Expert the physicians who used the program did not achieve as good results as the experts. The functionality of the programs was evaluated with questionnaires. According to this limited inquiry Sleep Expert could be used in clinical work, whereas Epilepsy Expert was regarded as being weaker. As a whole Sleep Expert was better than Epilepsy Expert. The conclusions to be drawn from the study are: In the development phase factors related to users, knowledge, problem definition and the environmental adaptation of the system need to be taken into account. If international classifications are to be used as a basis for the systems' knowledge, classification should be sufficiently clear and precise in respect of individual diagnoses.(ABSTRACT TRUNCATED AT 400 WORDS)

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癫痫和睡眠诊断的计算机辅助决策。
这项研究的主要目的是首先开发癫痫和睡眠障碍诊断决策支持系统的两个原型。第二个目标是在这些程序示例的帮助下检查医疗决策,并进一步评估决策支持系统应该设置哪些要求,以便在临床工作中找到自己的位置。首先为要开发的系统定义需求。大多数情况下,在开发过程中成功地考虑到了需求。随后开发了基于国际癫痫和癫痫综合征分类(51)的决策支持系统Epilepsy Expert。由于分类的性质,一名癫痫专家在发展工作中发挥了核心作用。对于睡眠障碍,sleep Expert是一个决策支持系统,是根据国际睡眠障碍分类开发的(52)。在系统的开发过程中,专家在睡眠障碍方面的作用较小,因为国际分类为程序知识提供了良好的基础。程序的知识验证如下。首先,三位专家被要求提供10个病例描述,然后他们对他们同事的病人进行诊断。在这些诊断的基础上,达成了多数人的共识,即“正确的诊断”。本文利用癫痫专家的决策树对同一例癫痫病例进行诊断。另外两名医生不是睡眠障碍方面的专家,他们使用sleep Expert对睡眠障碍进行了诊断。在验证中,癫痫专家证明部分不完整,部分原因是国际分类的弱点。然而,该程序中仅基于临床发现的诊断部分与专家一样好。在睡眠专家的验证中,使用该程序的医生没有达到专家那样好的效果。通过问卷对程序的功能进行评估。根据这一有限的调查,睡眠专家可以在临床工作中使用,而癫痫专家则被认为较弱。总的来说,睡眠专家比癫痫专家好。从研究中得出的结论是:在开发阶段,需要考虑与用户、知识、问题定义和系统的环境适应性有关的因素。如果要使用国际分类作为系统知识的基础,就个别诊断而言,分类应该足够清晰和准确。(摘要删节为400字)
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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Proceedings of the Annual Meeting of the Norwegian Neurological Association. November 2010. Oslo, Norway. Selected articles from the Annual Meeting of the Norwegian Neurological Association, November 2009, Oslo, Norway. Selected articles from the Annual Meeting of the Norwegian Neurological Association, 26-30 November 2007, Oslo, Norway. Advances in the pathophysiology of status epilepticus. Childhood convulsive status epilepticus: epidemiology, management and outcome.
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