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Year : 2021  |  Volume : 8  |  Issue : 2  |  Page : 41-48

Applications of artificial intelligence in epilepsy

1 Department of Neurology, JIPMER, Puducherry, India
2 Consultant Neurologist, Apollo Health City, Hyderabad, Telangana, India

Correspondence Address:
Dr. Pradeep Pankajakshan Nair
JIPMER, Puducherry
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijamr.ijamr_94_21

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Epilepsy is a common neurological condition characterized by a predilection for recurrent seizures. It affects 3.0–11.9 persons per 1000 in India. The advent of machine learning and artificial intelligence (AI) has allowed us to harness computing power to evaluate enormous amounts of data to provide more definitive answers to many vexing questions in epilepsy such as the nature of a paroxysmal event, prediction of seizure, response to therapy, etc. In this article, we present an overview of AI and machine learning approaches to the diagnosis and management of epilepsy. We performed a MEDLINE search with both keywords (AI, epilepsy, Epilepsy, Machine learning, seizure) and MeSH terms (AI, Seizures) combined with Boolean operators. We present a narrative summary of the results. We initially discuss basic concepts regarding AI and its divisions, followed by a discussion of the role of AI in epilepsy from published studies particularly in the areas of diagnosis and classification of epilepsy; seizure detection and prediction; epileptogenesis; and management of epilepsy. Despite the growing popularity of AI in epilepsy, it should be remembered that these approaches are not without drawbacks. All machine learning approaches are data expensive and require a large computational capacity. This also has a bearing on the time taken for the development of these algorithms. AI is here to stay and influence all aspects of care for people with epilepsy (PWE) and it is necessary to equip ourselves to interface with these smart systems. This balance will help provide the best possible care to PWE.

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