From classification to epilepsy ontology and informatics

Authors

  • Guo-Qiang Zhang,

    1. Division of Medical Informatics, Case Western Reserve University and University Hospitals Case Medical Center, Cleveland, Ohio, U.S.A.
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  • Satya S. Sahoo,

    1. Division of Medical Informatics, Case Western Reserve University and University Hospitals Case Medical Center, Cleveland, Ohio, U.S.A.
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  • Samden D. Lhatoo

    1. Department of Neurology, Case Western Reserve University and University Hospitals Case Medical Center, Cleveland, Ohio, U.S.A.
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Address correspondence to Samden D. Lhatoo, Case Western Reserve University and University Hospitals Case Medical Center, 11100 Euclid Avenue, Cleveland, OH 44106, U.S.A. E-mail: samden.lhatoo@uhhospitals.org

Summary

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.

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