AI Medical Compendium Journal:
Neuroscience

Showing 1 to 10 of 41 articles

Altered static and dynamic functional network connectivity and combined Machine learning in asthma.

Neuroscience
Asthma is a reversible disease characterized by airflow limitation and chronic airway inflammation. Previous neuroimaging studies have shown structural and functional abnormalities in the brains of individuals with asthma. However, earlier research h...

A review of multimodal fusion-based deep learning for Alzheimer's disease.

Neuroscience
Alzheimer's Disease (AD) as one of the most prevalent neurodegenerative disorders worldwide, characterized by significant memory and cognitive decline in its later stages, severely impacting daily lives. Consequently, early diagnosis and accurate ass...

Enhanced EEG-based Alzheimer's disease detection using synchrosqueezing transform and deep transfer learning.

Neuroscience
The most prevalent type of dementia and a progressive neurodegenerative disease, Alzheimer's disease has a major influence on day-to-day functioning due to memory loss, cognitive decline, and behavioral problems. By using synchrosqueezing representat...

A fully automatic radiomics pipeline for postoperative facial nerve function prediction of vestibular schwannoma.

Neuroscience
Vestibular schwannoma (VS) is the most prevalent intracranial schwannoma. Surgery is one of the options for the treatment of VS, with the preservation of facial nerve (FN) function being the primary objective. Therefore, postoperative FN function pre...

Deep learning for cerebral vascular occlusion segmentation: A novel ConvNeXtV2 and GRN-integrated U-Net framework for diffusion-weighted imaging.

Neuroscience
Cerebral vascular occlusion is a serious condition that can lead to stroke and permanent neurological damage due to insufficient oxygen and nutrients reaching brain tissue. Early diagnosis and accurate segmentation are critical for effective treatmen...

Letters to the editor generated by AI in neuroscience: The role of neuroethics.

Neuroscience
The letter to the editor (LTE) is a correspondence forum that allows a journal's readers to comment on published research and also publish data and arguments in a brief way. The LTE has vital functions as an accessible comment forum, including holdin...

Transforming neurodegenerative disorder care with machine learning: Strategies and applications.

Neuroscience
Neurodegenerative diseases (NDs), characterized by progressive neuronal degeneration and manifesting in diverse forms such as memory loss and movement disorders, pose significant challenges due to their complex molecular mechanisms and heterogeneous ...

Artificial intelligence in stroke rehabilitation: From acute care to long-term recovery.

Neuroscience
Stroke is a leading cause of disability worldwide, driving the need for advanced rehabilitation strategies. The integration of Artificial Intelligence (AI) into stroke rehabilitation presents significant advancements across the continuum of care, fro...

Development and validation of radiomics and deep transfer learning models to assess cognitive impairment in patients with cerebral small vessel disease.

Neuroscience
Cognitive impairment in cerebral small vessel disease (CSVD) progresses subtly but carries significant clinical consequences, necessitating effective diagnostic tools. This study developed and validated predictive models for CSVD-related cognitive im...

Use of deep learning-based high-resolution magnetic resonance to identify intracranial and extracranial symptom-related plaques.

Neuroscience
This study aims to develop a deep learning model using high-resolution vessel wall imaging (HR-VWI) to differentiate symptom-related intracranial and extracranial plaques, which is crucial for stroke treatment and prevention. We retrospectively analy...