{"title":"人工智能在癫痫中的应用及临床路径","authors":"Alfredo Lucas, Andrew Revell, Kathryn A. Davis","doi":"10.1038/s41582-024-00965-9","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":19085,"journal":{"name":"Nature Reviews Neurology","volume":"20 6","pages":"319-336"},"PeriodicalIF":28.2000,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence in epilepsy — applications and pathways to the clinic\",\"authors\":\"Alfredo Lucas, Andrew Revell, Kathryn A. Davis\",\"doi\":\"10.1038/s41582-024-00965-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":19085,\"journal\":{\"name\":\"Nature Reviews Neurology\",\"volume\":\"20 6\",\"pages\":\"319-336\"},\"PeriodicalIF\":28.2000,\"publicationDate\":\"2024-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature Reviews Neurology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.nature.com/articles/s41582-024-00965-9\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Reviews Neurology","FirstCategoryId":"3","ListUrlMain":"https://www.nature.com/articles/s41582-024-00965-9","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
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.
期刊介绍:
Nature Reviews Neurology aims to be the premier source of reviews and commentaries for the scientific and clinical communities we serve. We want to provide an unparalleled service to authors, referees, and readers, and we work hard to maximize the usefulness and impact of each article. The journal publishes Research Highlights, Comments, News & Views, Reviews, Consensus Statements, and Perspectives relevant to researchers and clinicians working in the field of neurology. Our broad scope ensures that the work we publish reaches the widest possible audience. Our articles are authoritative, accessible, and enhanced with clearly understandable figures, tables, and other display items. This page gives more detail about the aims and scope of the journal.