Emerging Frontiers of Artificial Intelligence in Epilepsy Care: A Comprehensive Overview

Epilepsy, a chronic neurological disorder characterized by recurrent seizures, poses significant challenges in diagnosis, treatment, and management. In recent years, Artificial Intelligence (AI) has emerged as a promising tool to revolutionize various aspects of epilepsy care. This comprehensive review explores the advancements and applications of AI in epilepsy, encompassing diagnostic support, seizure prediction, personalized treatment strategies, and therapeutic monitoring. AI techniques such as machine learning, deep learning, and natural language processing are leveraged to analyze diverse datasets including electroencephalogram (EEG) recordings, imaging studies, genetic data, and clinical records. Key applications include automated seizure detection and classification systems, predictive models for personalized treatment plans, and real-time monitoring tools to enhance patient management. Furthermore, AI-driven approaches enable integration of multimodal data to improve accuracy and reliability in epilepsy diagnosis and prognosis. Challenges such as data heterogeneity, interpretability of AI models, ethical considerations, and regulatory issues are also discussed. This review highlights the transformative potential of AI in advancing epilepsy research and clinical practice, offering insights into future directions for leveraging AI to optimize care and improve outcomes for individuals living with epilepsy.

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Publication Details

Published
2024-11-29
DOI
https://doi.org/10.1109/idicaiei61867.2024.10842843
Citations
1
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.34
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Emerging Frontiers of Artificial Intelligence in Epilepsy Care: A Comprehensive Overview

P. Moon, Byungin Moon, N Chaudhary, Shubhangi S. Shambharkar et al.
1 citations
EEG and Brain-Computer Interfaces
0.34
article

Emerging Frontiers of Artificial Intelligence in Epilepsy Care: A Comprehensive Overview

P. Moon, Byungin Moon, N Chaudhary, Shubhangi S. Shambharkar, Prachi A. Bainalwar
article en
1 citations

Abstract

Epilepsy, a chronic neurological disorder characterized by recurrent seizures, poses significant challenges in diagnosis, treatment, and management. In recent years, Artificial Intelligence (AI) has emerged as a promising tool to revolutionize various aspects of epilepsy care. This comprehensive review explores the advancements and applications of AI in epilepsy, encompassing diagnostic support, seizure prediction, personalized treatment strategies, and therapeutic monitoring. AI techniques such as machine learning, deep learning, and natural language processing are leveraged to analyze diverse datasets including electroencephalogram (EEG) recordings, imaging studies, genetic data, and clinical records. Key applications include automated seizure detection and classification systems, predictive models for personalized treatment plans, and real-time monitoring tools to enhance patient management. Furthermore, AI-driven approaches enable integration of multimodal data to improve accuracy and reliability in epilepsy diagnosis and prognosis. Challenges such as data heterogeneity, interpretability of AI models, ethical considerations, and regulatory issues are also discussed. This review highlights the transformative potential of AI in advancing epilepsy research and clinical practice, offering insights into future directions for leveraging AI to optimize care and improve outcomes for individuals living with epilepsy.

Datta Meghe Institute of Higher Education and Research (IN)
Openalex Percentile: Top 37%
EEG and Brain-Computer Interfaces
0.34
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Emerging Frontiers of Artificial Intelligence in Epilepsy Care: A Comprehensive Overview — P. Moon, Byungin Moon, et al. · (2024) | TGRS Research Map | TGRS