AIMC Topic: Seizures
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Predicting EEG seizures using graded spiking neural networks.
Journal of neural engineering
Mar 6, 2025
To develop and evaluate a novel, non-patient-specific epileptic seizure prediction system using graded spiking neural networks (GSNNs) implemented on Intel's Loihi 2 neuromorphic processor, addressing the challenges of real-time, energy-efficient pre...
Real-Time Epileptic Seizure Prediction Method With Spatio-Temporal Information Transfer Learning.
IEEE journal of biomedical and health informatics
Mar 6, 2025
Despite numerous studies aimed at improving accuracy, the accurate prediction of epileptic seizures remains a challenge in clinical practice due to the high computational cost, poor real-time performance, and over-reliance on labelled data. To addres...
Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine.
Epilepsy & behavior : E&B
Mar 4, 2025
Artificial intelligence (AI) is revolutionizing epilepsy care by advancing seizure detection, enhancing diagnostic precision, and enabling personalized treatment. Machine learning and deep learning technologies improve seizure monitoring, automate EE...
SeizyML: An Application for Semi-Automated Seizure Detection Using Interpretable Machine Learning Models.
Neuroinformatics
Mar 3, 2025
Despite the vast number of publications reporting seizures and the reliance of the field on accurate seizure detection, there is a lack of open-source software tools in the scientific community for automating seizure detection based on electrographic...
Inductive reasoning with large language models: A simulated randomized controlled trial for epilepsy.
Epilepsy research
Feb 24, 2025
INTRODUCTION: To investigate the potential of using artificial intelligence (AI), specifically large language models (LLMs), for synthesizing information in a simulated randomized clinical trial (RCT) for an anti-seizure medication, cenobamate, demon...
Machine learning based seizure classification and digital biosignal analysis of ECT seizures.
Scientific reports
Feb 21, 2025
While artificial intelligence has received considerable attention in various medical fields, its application in the field of electroconvulsive therapy (ECT) remains rather limited. With the advent of digital seizure collection systems, the developmen...
Integrating manual preprocessing with automated feature extraction for improved rodent seizure classification.
Epilepsy & behavior : E&B
Feb 20, 2025
HYPOTHESIS/OBJECTIVE: Rodent models of epilepsy can help with the search for more effective drug candidates or neuromodulatory therapies. Yet, preclinical screening of candidate options for anti-epileptic drugs (AED) using rodent models may require h...
Supervised machine learning compared to large language models for identifying functional seizures from medical records.
Epilepsia
Feb 17, 2025
OBJECTIVE: The Functional Seizures Likelihood Score (FSLS) is a supervised machine learning-based diagnostic score that was developed to differentiate functional seizures (FS) from epileptic seizures (ES). In contrast to this targeted approach, large...
BrainForest: Neuromorphic Multiplier-Less Bit-Serial Weight-Memory-Optimized 1024-Tree Brain-State Classification Processor.
IEEE transactions on biomedical circuits and systems
Feb 11, 2025
Personalized brain implants have the potential to revolutionize the treatment of neurological disorders and augment cognition. Medical implants that deliver therapeutic stimulation in response to detected seizures have already been deployed for the t...
Low-Power and Low-Cost AI Processor With Distributed-Aggregated Classification Architecture for Wearable Epilepsy Seizure Detection.
IEEE transactions on biomedical circuits and systems
Feb 11, 2025
Wearable devices with continuous monitoring capabilities are critical for the daily detection of epileptic seizures, as they provide users with accurate and comprehensible analytical results. However, current AI classifiers rely on a two-stage recogn...
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