Neurology

Latest AI and machine learning research in neurology for healthcare professionals.

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Multimodal AI diagnostic system for neuromyelitis optica based on ultrawide-field fundus photography.

PURPOSE: While deep learning (DL) has demonstrated significant utility in ocular diseases, no clinic...

AD-AutoGPT: An autonomous GPT for Alzheimer's disease infodemiology.

In this pioneering study, inspired by AutoGPT, the state-of-the-art open-source application based on...

Enhancing Neurodegenerative Disease Diagnosis Through Confidence-Driven Dynamic Spatio-Temporal Convolutional Network.

Dynamic brain networks are more effective than static networks in characterizing the evolving patter...

Efficient, Robust, and Accurate CNN Predictor for Neuronal Activation in Directional Deep Brain Stimulation.

The programming of clinical deep brain stimulation (DBS) systems involves numerous combinations of s...

Tailored pharmacotherapy monitoring in Parkinson's disease and Schizophrenia using a rapid and sensitive α-Synuclein assay.

BACKGROUND: While Parkinson's disease is a low dopamine neurodegenerative disorder, Schizophrenia is...

Biocatalytic production of a monoamine oxidase B/catechol-O-methyltransferase inhibitor from piperine by engineered P450 BM3.

The single-step biotransformation of the natural compound piperine into a known dual inhibitor of mo...

AI-assisted ophthalmic imaging for early detection of neurodegenerative diseases.

BACKGROUND: Artificial intelligence (AI) plays a promising role in ophthalmic imaging by providing i...

Unveiling new insights into migraine risk stratification using machine learning models of adjustable risk factors.

BACKGROUND: Migraine ranks as the second-leading cause of global neurological disability, affecting ...

Diagnosing migraine from genome-wide genotype data: a machine learning analysis.

Migraine has an assumed polygenic basis, but the genetic risk variants identified in genome-wide ass...

AI-Generated Ammonium Ligands for High-Efficiency and Stable 2D/3D Heterojunction Perovskite Solar Cells.

The 2D/3D heterojunction perovskite solar cells (PSCs) exhibit remarkable stability, but the quantum...

CrossConvPyramid: Deep Multimodal Fusion for Epileptic Magnetoencephalography Spike Detection.

Magnetoencephalography (MEG) is a vital non-invasive tool for epilepsy analysis, as it captures high...

Unsupervised Domain Adaptation With Synchronized Self-Training for Cross- Domain Motor Imagery Recognition.

Robust decoding performance is essential for the practical deployment of brain-computer interface (B...

A Distributed Neural Network Architecture for Dynamic Sensor Selection With Application to Bandwidth-Constrained Body-Sensor Networks.

We propose a dynamic sensor selection approach for deep neural networks (DNNs), which is able to der...

AI-driven early diagnosis of specific mental disorders: a comprehensive study.

One of the areas where artificial intelligence (AI) technologies are used is the detection and diagn...

Entropy-driven deep learning framework for epilepsy detection using electro encephalogram signals.

Epilepsy is one of the most frequently occurring neurological disorders that require early and accur...

A Novel 3D Approach with a CNN and Swin Transformer for Decoding EEG-Based Motor Imagery Classification.

Motor imagery (MI) is a crucial research field within the brain-computer interface (BCI) domain. It ...

Optimizing Stroke Risk Prediction: A Primary Dataset-Driven Ensemble Classifier With Explainable Artificial Intelligence.

BACKGROUND AND AIMS: Stroke remains a leading cause of mortality and long-term disability worldwide,...

Classification of Neuropsychiatric Disorders via Brain-Region-Selected Graph Convolutional Network.

For the classification of patients with neuropsychiatric disorders based on rs-fMRI data, this paper...

Development and Validation of the Novel Exergame-Integrated Robotic Stepper Device for Seated Lower Limb Rehabilitation.

Seated rehabilitation is essential in early-stage recovery for patients who can sit but cannot stand...

Use of posterior probabilities from a long short-term memory network for characterizing dance behavior with multiple accelerometers.

BackgroundDancing may be protective for cognitive health among adults with mild cognitive impairment...

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