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Artificial Intelligence in Epilepsy: Advances in Diagnosis and Treatment

Edited by:

Edward Meinert, PhD, Newcastle University, United Kingdom
Gavin Winston, MD, Queen's University, Canada

Submission Status: Open   |   Submission Deadline: 28 February 2025

Acta Epileptologica is calling for submissions to our Collection on Artificial Intelligence in Epilepsy: Advances in Diagnosis and Treatment.

Image credit: © Teeradej /

New Content ItemThis Collection supports and amplifies research related to SDG 3: Good Health & Wellbeing.

Meet the Guest Editors

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Professor Edward Meinert, MA MSc MBA MPA MPH PhD CEng FBCS, Translational and Clinical Research Institute, Newcastle Unviersity, United Kingdom 

Professor Edward Meinert conducts research on the design and evaluation of digital technology in healthcare. His research interests include clinical artificial intelligence, robotic process automation, and digital health, with a goal of enhancing population health, particularly in novel regulatory and therapeutic contexts like preventive medicine. Prof. Meinert aims to generate evidence for refining technology design and influencing policy to foster the adoption of systems with beneficial health outcomes.  

Professor Gavin Winston, MA, MD, MBA, PhD, Queen’s University, Canada

Dr. Gavin Winston is a Professor at Queen’s University, specializing in neurology and neuroimaging. His research focuses on rapid seizure assessment, treatment of refractory focal epilepsy, and computational neuroimaging to enhance epilepsy surgery outcomes. He founded the First Seizure Clinic at Kingston Health Sciences Centre and contributes to international studies like MELD and ENIGMA Epilepsy. Dr. Winston aims to improve patient care through innovative imaging techniques and predictive models for seizure recurrence.

About the Collection

Artificial Intelligence (AI) has affected many aspects of human life, including the diagnosis and treatment of brain diseases. It has been increasingly applied in brain imaging and analysis, brain network research, and big data processing of disease queues, improving the classification of clinical diagnosis subtypes, prediction of treatment effects, and understanding and judgment of comorbidity. The application of AI technology is expected to provide more accurate and timely diagnosis and treatment for epilepsy patients. As a professional medical journal on epilepsy, Acta Epileptologica focuses on the latest advances in AI and epilepsy treatment, and provides an academic platform for all researchers and readers to share research findings and perspectives related to artificial intelligence and epilepsy treatment.

Acta Epileptologica is an open access medical journal in the field of epilepsy, which covers all aspects of the prevention, diagnosis, treatment, and management of epilepsy, as well as the basic research and translational research. It is currently seeking high-quality, innovative manuscripts focused the relationship between AI and epilepsy diagnosis and therapy to be published.

The recommending themes (not limited):

(1) Research progress, clinical application and future trend analysis of AI and big data technology in the field of epilepsy;

(2) Research on innovative methods and application of AI in epilepsy diagnosis;

(3) Application of AI in epileptic MRI, PET and CT image processing;

(4) Application of AI in epileptic EEG and MEG signal analysis;

(5) Application of AI technology in the treatment and regulation of epilepsy;

(6) Study on the mechanism of AI in epilepsy network;

(7) Application of AI technology in brain function protection;

(8) The application and practice of the internet and big data in clinical epilepsy;

(9) The role of AI in addressing current health inequities and the potential challenges that may arise. 

  1. Epilepsy is a common chronic neurological disease. Its repeated seizure attacks have a great negative impact on patients’ physical and mental health. The diagnosis of epilepsy mainly depends on electroencephal...

    Authors: Lijun Li, Hengxing Zhang, Xiaomei Liu, Jie Li, Lei Li, Dan Liu, Jieqing Min, Ping Zhu, Huan Xia, Shangkun Wang and Li Wang
    Citation: Acta Epileptologica 2023 5:7

    The Correction to this article has been published in Acta Epileptologica 2023 5:9

  2. The KCNT1 gene encodes a Na+-activated K+ channel. Gain-of-function mutations of KCNT1 lead to autosomal dominant sleep-related hypermotor epilepsy, early-onset epileptic encephalopathy, focal epilepsy and other ...

    Authors: Meng Wang, Guifu Geng, Yao Meng, Hongwei Zhang, Zaifen Gao and Jianguo Shi
    Citation: Acta Epileptologica 2022 4:34

Submission Guidelines

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This Collection welcomes submission of Research Reviews, Case Reports, Consensus and Commentaries. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal.

Articles for this Collection should be submitted via our submission system, Editorial Manager. Please select the appropriate Collection title “Artificial Intelligence in Epilepsy: Advances in Diagnosis and Treatment" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer-review process. The peer-review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.