From classification to epilepsy ontology and informatics.
From classification to epilepsy ontology and informatics.
复制标题
从分类到癫痫本体论和信息学。
DOI：
10.1111/j.1528-1167.2012.03556.x
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发表时间：
2012
期刊：
影响因子：
5.6
通讯作者：
Lhatoo,SamdenD
中科院分区：
文献类型：
--
作者：
Zhang,Guo-Qiang;Sahoo,SatyaS;Lhatoo,SamdenD
2010年国际抗癫痫联盟（ILAE）分类和术语委员会报告提出了一个非常需要的偏离以前的分类，以纳入分子生物学，神经影像学和遗传学的进展。它提出了一个临时分类，并确定了需要满足的两个关键要求。首先是能够根据各种目的，包括临床研究，患者护理和药物发现，对癫痫进行维度分类。第二是分类系统随着新发现而发展的能力。多维性和灵活性对于未来任何分类的成功至关重要。此外，一个成功的分类系统必须在迅速发展的癫痫信息学领域发挥核心作用。基于分类的癫痫本体将允许信息系统促进数据密集型研究，并提供满足上述两个关键要求的经过验证的途径。癫痫本体将是一个结构化的术语系统，它适应拟议的和不断发展的ILAE分类，美国国立卫生研究院/国家神经疾病和中风研究所（NIH/NINDS）共同数据元素，国际疾病分类（ICD）系统，并明确规定在适当的框架中癫痫概念之间的所有已知关系。这将有助于基于证据的癫痫诊断，调查，治疗和研究的临床医生和研究人员的多样化社区。受益范围从电子病历的系统化到用于癫痫护理研究和培训手册的多模式数据存储库。鉴于癫痫领域的复杂性，异质性和研究进展的步伐，这样的本体论必须由癫痫社区的关键利益相关者和知识工程和计算机科学的专家合作开发。
The 2010 International League Against Epilepsy (ILAE) classification and terminology commission report proposed a much needed departure from previous classifications to incorporate advances in molecular biology, neuroimaging, and genetics. It proposed an interim classification and defined two key requirements that need to be satisfied. The first is the ability to classify epilepsy in dimensions according to a variety of purposes including clinical research, patient care, and drug discovery. The second is the ability of the classification system to evolve with new discoveries. Multidimensionality and flexibility are crucial to the success of any future classification. In addition, a successful classification system must play a central role in the rapidly growing field of epilepsy informatics. An epilepsy ontology, based on classification, will allow information systems to facilitate data‐intensive studies and provide a proven route to meeting the two foregoing key requirements. Epilepsy ontology will be a structured terminology system that accommodates proposed and evolving ILAE classifications, the National Institutes of Health/National Institute of Neurological Disorders and Stroke (NIH/NINDS) Common Data Elements, the International Classification of Diseases (ICD) systems and explicitly specifies all known relationships between epilepsy concepts in a proper framework. This will aid evidence‐based epilepsy diagnosis, investigation, treatment and research for a diverse community of clinicians and researchers. Benefits range from systematization of electronic patient records to multimodal data repositories for research and training manuals for those involved in epilepsy care. Given the complexity, heterogeneity, and pace of research advances in the epilepsy domain, such an ontology must be collaboratively developed by key stakeholders in the epilepsy community and experts in knowledge engineering and computer science.