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Machine Learning and Artificial Intelligence Applications to Epilepsy: a Review for the Practicing Epileptologist.

作者信息

Kerr Wesley T, McFarlane Katherine N

机构信息

Department of Neurology, University of Pittsburgh, 3471 Fifth Ave, Kaufmann 811.22, Pittsburgh, PA, 15213, USA.

Department of Biomedical Informatics, University of Pittsburgh, 3471 Fifth Ave, Kaufmann 811.22, Pittsburgh, PA, 15213, USA.

出版信息

Curr Neurol Neurosci Rep. 2023 Dec;23(12):869-879. doi: 10.1007/s11910-023-01318-7. Epub 2023 Dec 7.


DOI:10.1007/s11910-023-01318-7
PMID:38060133
Abstract

PURPOSE OF REVIEW: Machine Learning (ML) and Artificial Intelligence (AI) are data-driven techniques to translate raw data into applicable and interpretable insights that can assist in clinical decision making. Some of these tools have extremely promising initial results, earning both great excitement and creating hype. This non-technical article reviews recent developments in ML/AI in epilepsy to assist the current practicing epileptologist in understanding both the benefits and limitations of integrating ML/AI tools into their clinical practice. RECENT FINDINGS: ML/AI tools have been developed to assist clinicians in almost every clinical decision including (1) predicting future epilepsy in people at risk, (2) detecting and monitoring for seizures, (3) differentiating epilepsy from mimics, (4) using data to improve neuroanatomic localization and lateralization, and (5) tracking and predicting response to medical and surgical treatments. We also discuss practical, ethical, and equity considerations in the development and application of ML/AI tools including chatbots based on Large Language Models (e.g., ChatGPT). ML/AI tools will change how clinical medicine is practiced, but, with rare exceptions, the transferability to other centers, effectiveness, and safety of these approaches have not yet been established rigorously. In the future, ML/AI will not replace epileptologists, but epileptologists with ML/AI will replace epileptologists without ML/AI.

摘要

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引用本文的文献

[1]
Artificial intelligence in electroencephalography analysis for epilepsy diagnosis and management.

Front Neurol. 2025-8-18

[2]
Advancements and Challenges of Artificial Intelligence-Assisted Electroencephalography in Epilepsy Management.

J Clin Med. 2025-6-16

[3]
Interpretable multiparametric MRI radiomics-based machine learning model for preoperative differentiation between benign and malignant prostate masses: a diagnostic, multicenter study.

Front Oncol. 2025-5-5

[4]
Innovating pediatric epilepsy: transforming diagnosis and treatment with AI.

World J Pediatr. 2025-5-4

[5]
The use of AI in epilepsy and its applications for people with intellectual disabilities: commentary.

Acta Epileptol. 2025-2-19

[6]
Electroencephalography-driven brain-network models for personalized interpretation and prediction of neural oscillations.

Clin Neurophysiol. 2025-6

[7]
A comprehensive evaluation of interpretable artificial intelligence for epileptic seizure diagnosis using an electroencephalogram: A systematic review.

Digit Health. 2025-3-13

[8]
Towards precision MRI biomarkers in epilepsy with normative modelling.

Brain. 2025-7-7

[9]
Supervised machine learning compared to large language models for identifying functional seizures from medical records.

Epilepsia. 2025-4

[10]
Can ChatGPT 4.0 Diagnose Epilepsy? A Study on Artificial Intelligence's Diagnostic Capabilities.

J Clin Med. 2025-1-7

本文引用的文献

[1]
Implementation and impact of a point of care electroencephalography platform in a community hospital: a cohort study.

Front Digit Health. 2023-8-7

[2]
Optimizing detection and deep learning-based classification of pathological high-frequency oscillations in epilepsy.

Clin Neurophysiol. 2023-10

[3]
Rapid-Response Electroencephalography in Seizure Diagnosis and Patient Care: Lessons From a Community Hospital.

J Neurosci Nurs. 2023-10-1

[4]
Accuracy of Chatbots in Citing Journal Articles.

JAMA Netw Open. 2023-8-1

[5]
Machine-learning for the prediction of one-year seizure recurrence based on routine electroencephalography.

Sci Rep. 2023-8-4

[6]
Deep learning in neuroimaging of epilepsy.

Clin Neurol Neurosurg. 2023-9

[7]
Point-of-care electroencephalography enables rapid evaluation and management of non-convulsive seizures and status epilepticus in the emergency department.

J Am Coll Emerg Physicians Open. 2023-7-15

[8]
Putting ChatGPT's Medical Advice to the (Turing) Test: Survey Study.

JMIR Med Educ. 2023-7-10

[9]
Artificial Intelligence in Clinical Diagnosis: Opportunities, Challenges, and Hype.

JAMA. 2023-7-25

[10]
Disparities in adherence and emergency department utilization among people with epilepsy: A machine learning approach.

Seizure. 2023-8

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