Artificial intelligence in epilepsy - applications and pathways to the clinic

Artificial intelligence (AI) is rapidly transforming health care, and its applications in epilepsy have increased exponentially over the past decade. Integration of AI into epilepsy management promises to revolutionize the diagnosis and treatment of this complex disorder. However, translation of AI into neurology clinical practice has not yet been successful, emphasizing the need to consider progress to date and assess challenges and limitations of AI. In this Review, we provide an overview of AI applications that have been developed in epilepsy using a variety of data modalities: neuroimaging, electroencephalography, electronic health records, medical devices and multimodal data integration. For each, we consider potential applications, including seizure detection and prediction, seizure lateralization, localization of the seizure-onset zone and assessment for surgical or neurostimulation interventions, and review the performance of AI tools developed to date. We also discuss methodological considerations and challenges that must be addressed to successfully integrate AI into clinical practice. Our goal is to provide an overview of the current state of the field and provide guidance for leveraging AI in future to improve management of epilepsy. Integration of artificial intelligence into epilepsy management could revolutionize diagnosis and treatment. In this Review, the authors provide an overview of artificial intelligence applications that have been developed in epilepsy and discuss challenges that must be addressed to successfully integrate artificial intelligence into clinical practice. Artificial intelligence (AI) has the potential to maximize the value of data collected throughout the management of epilepsy, including neuroimaging and electroencephalography data, electronic medical records, and data from medical devices.Machine learning dominated early applications of AI in epilepsy, but deep learning approaches have become increasingly popular.Despite development of many AI tools with potential for the diagnosis and management of epilepsy, few have been implemented in clinical practice.Collaborative efforts, including sharing of data and expertise, among researchers and clinicians are essential to realize the full potential of AI in epilepsy management.Methodological and ethical considerations are pivotal for integrating AI into routine epilepsy management.Future advancements in AI require robust clinical trials and ethical frameworks to ensure efficacy and patient safety in epilepsy treatment.