Treffer: A call for ethical, equitable, and effective artificial intelligence to improve care for all people with epilepsy: A roadmap. A report by the ILAE Global Advocacy Council and Big Data Commission.
Title:
A call for ethical, equitable, and effective artificial intelligence to improve care for all people with epilepsy: A roadmap. A report by the ILAE Global Advocacy Council and Big Data Commission.
Authors:
Josephson CB; Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.; O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada.; Centre for Health Informatics, University of Calgary, Calgary, Alberta, Canada.; Institute of Health Informatics, University College London, London, UK., Beniczky S; Department of Clinical Neurophysiology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark.; Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark.; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark., Denaxas S; Institute of Health Informatics, University College London, London, UK.; British Heart Foundation Data Science Center, Health Data Research UK, London, UK., Ikeda A; Department of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine Shogoin, Sakyo-ku Kyoto, Japan., Jehi L; Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA.; Computational Life Sciences, Cleveland Clinic Research, Cleveland Clinic, Cleveland, Ohio, USA., Mwesige AK; Department of Paediatrics and Child Health, Makerere University College of Health Sciences, Kampala, Uganda.; Department of Paediatrics and Child Health, Mulago National Referral Hospital, Pediatric Neurology Unit, Kampala, Uganda., Jette N; Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.; O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada., Jones GD; Oxford Digital Health Labs, Nuffield Department of Women's and Reproductive Health, John Radcliffe Hospital, University of Oxford, Oxford, UK., Ryvlin P; Department of Clinical Neurosciences, Centre Hospital-Universitaire Vaudois and Université de Lausanne, Lausanne, Switzerland.; Member of European Reference Network EpiCARE, London, UK., Sen A; Oxford Epilepsy Research Group, Nuffield Department of Clincial Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, UK.; Centre for Global Epilepsy, Wolfson College, University of Oxford, Oxford, UK., Triki CC; Child Neurology Department, LR19ES15, Sfax Medical School, University of Sfax, Sfax, Tunisia., Waters G; Department of Electrical Engineering and Center for Equitable Artificial Intelligence and Machine Learning Systems, Morgan State University, Baltimore, Maryland, USA., Guekht A; Moscow Research and Clinical Center for Neuropsychiatry, Moscow, Russian Federation.; Pirogov Russian National Research University, Moscow, Russian Federation., Cross JH; UCL NIHR BRC Great Ormond Street Institute of Child Health, London, UK.; Great Ormond Street Hospital for Children, London, UK.
Source:
Epilepsia [Epilepsia] 2025 Dec 24. Date of Electronic Publication: 2025 Dec 24.
Publication Model:
Ahead of Print
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Blackwell Science Country of Publication: United States NLM ID: 2983306R Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1528-1167 (Electronic) Linking ISSN: 00139580 NLM ISO Abbreviation: Epilepsia Subsets: MEDLINE
Imprint Name(s):
Publication: Malden, MA : Blackwell Science
Original Publication: Copenhagen : Munskgaard
Original Publication: Copenhagen : Munskgaard
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Contributed Indexing:
Keywords: AI ethics; Intersectoral Global Action Plan; computational intelligence; data science; deep learning; machine intelligence; machine learning; synthetic intelligence
Entry Date(s):
Date Created: 20251224 Latest Revision: 20251224
Update Code:
20251225
DOI:
10.1002/epi.70058
PMID:
41443971
Database:
MEDLINE
Weitere Informationen
The artificial intelligence (AI) revolution is upon us. It will inevitably form a central component of epilepsy workflows and patient advocacy. Therefore, it behooves us as health care providers to ride the crest of this wave and guide its direction for the benefit of all people with epilepsy. Emerging AI-based solutions include decision support tools, automated interpretation of electroencephalography (EEG) and brain imaging, and wearable devices that detect seizures and improve patient safety. Pipelines, including decentralized approaches and federated learning, are now being built that will democratize access and facilitate the next generation of AI tools for the global epilepsy community. Despite this, enduring issues remain incompletely addressed. For example, AI requires high volumes of data, leading to concerns about ethical ownership, stewardship, and privacy. Few AI-based tools have progressed from derivation to validation stages, and only rare exceptions undergo real-world evaluation. Inadvertent harmful algorithmic and decision allocation biases also continue to represent major risks to the global epilepsy population. Additional barriers include geographical disparities in computing resources, proprietary ownership of electronic health records, EEG, and brain-imaging platforms, and greenhouse gas emissions related to the demanding power requirements of AI. Therefore, to fully avail ourselves of the benefits of AI, we assert that ethical, equitable, and effective AI for epilepsy requires collaboration from the entirety of the global epilepsy community. Fundamental to this is early and deliberate engagement of people from low- and middle-income countries to ensure that AI-based solutions do not exacerbate existing global disparities. Ultimately, we advocate for "decision intelligence" approaches to the development of AI-based epilepsy solutions, which involves early engagement of all interest-holders to ensure that the correct questions are addressed and the right technical approaches are deployed to maximize value for the global epilepsy community.
(© 2025 The Author(s). Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)