AIMC Journal:
Developmental neurobiology
Showing 1 to 8 of 8 articles
An Effective LRSF-DLNN-Based Autism Spectrum Disorder Prediction Using EEG and fMRI.
Developmental neurobiology
Jul 1, 2026
In today's society, autism spectrum disorder (ASD) is a common neurological disorder that affects a person's behavior and communication. Hence, an early ASD prediction is essential for improving the lifecycle of ASD patients. Recently, many works hav...
An Enhanced Machine Learning-Based Multimodal Framework for Seizure Detection Using EEG and MRI Data.
Developmental neurobiology
Jul 1, 2026
One of the most common neurological disorders that immediately alters a person's way of life is an epileptic seizure. Accurate seizure detection remains a major challenge in neurological research due to the nonstationary and complex nature of electro...
Cloud EEG Privacy Using Red-Billed Blue Magpie Optimized Physics-Penalized Dual-Branch Spectral-Spatial Neural Network for Epileptic Seizure Prediction.
Developmental neurobiology
Jul 1, 2026
Epileptic seizure prediction is a critical research area that enables timely intervention and prevention of severe neurological complications. With the growing integration of IoT in healthcare, real-time EEG monitoring has become essential for contin...
A Robust Computational Framework for Autism Spectrum Disorder Identification Using Optimized Image Processing and Hybrid Learning Models.
Developmental neurobiology
Apr 1, 2026
The classification of autism spectrum disorder (ASD) has reached a new stage of development that includes the former machine learning (ML) designs and image analysis designs. The study introduces a new framework that uses discrete wavelet transformat...
Improved Hybrid Local Binary Structural Pattern Shallow Graph Deep Convolutional Attention Neural Networks With Synergistic Fibroblast Optimization for Automated Epileptic Seizure Detection and Diagnosis in EEG Signals.
Developmental neurobiology
Apr 1, 2026
Epileptic seizure (ES) detection from electroencephalography (EEG) signals is difficult because of noise and the intricate, patient-specific nature of brain activity. Traditional methods often suffer from low accuracy, high computational costs, and p...
Optimized Seizure Detection in EEG Using Dual-Branch Feature Fusion and Machine Learning Technique.
Developmental neurobiology
Apr 1, 2026
Epilepsy is a neurological disorder of the brain that generates seizures due to abnormal electrical activity. The diagnosis and management of the disease primarily depend on recordings of the EEG. A multistage methodology for seizure detection with e...
Channel Transformer-Based Generative Adversarial Network With Multi-Instance Attention and Nutcracker Optimization for Automatic Seizure Detection Using EEG.
Developmental neurobiology
Apr 1, 2026
The current literature on automatic seizure detection based on EEG has obtained significant accuracy, but most of them still have difficulties in processing the highly non-linear, non-stationary, and patient-specific EEG signals. Models typically nee...
Energy-Efficient EEG-Based Autism Spectrum Disorder Detection Using a Hyperbolic Attention Neural Network.
Developmental neurobiology
Apr 1, 2026
Long-term physiological monitoring using wearable wireless systems represents a paradigm change in next-generation e-health applications. Specifically, electroencephalography (EEG) represents a noninvasive and trustworthy way of recording brain activ...
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