AIMC Topic: Neuroimaging

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Dynamic Graph Representation Learning for Spatio-Temporal Neuroimaging Analysis.

IEEE transactions on cybernetics Mar 6, 2025
Neuroimaging analysis aims to reveal the information-processing mechanisms of the human brain in a noninvasive manner. In the past, graph neural networks (GNNs) have shown promise in capturing the non-Euclidean structure of brain networks. However, e...
Neuroimaging Humans Neural Networks, Computer Algorithms Brain Spatio-Temporal Analysis Image Processing, Computer-Assisted
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A Lightweight Deep Convolutional Neural Network Extracting Local and Global Contextual Features for the Classification of Alzheimer's Disease Using Structural MRI.

IEEE journal of biomedical and health informatics Mar 6, 2025
Recent advancements in the classification of Alzheimer's disease have leveraged the automatic feature generation capability of convolutional neural networks (CNNs) using neuroimaging biomarkers. However, most of the existing CNN-based methods often d...
Neural Networks, Computer Databases, Factual Brain Humans Alzheimer Disease Image Interpretation, Computer-Assisted Neuroimaging Deep Learning Convolutional Neural Networks Magnetic Resonance Imaging
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Improving ALS detection and cognitive impairment stratification with attention-enhanced deep learning models.

Scientific reports Feb 27, 2025
Amyotrophic lateral sclerosis (ALS) is a fatal neurological disease marked by motor deterioration and cognitive decline. Early diagnosis is challenging due to the complexity of sporadic ALS and the lack of a defined risk population. In this study, we...
Cognitive Dysfunction Humans Amyotrophic Lateral Sclerosis Frontotemporal Dementia Attention Neural Networks, Computer Early Diagnosis Middle Aged Neuroimaging Brain Female Deep Learning Aged Male
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Characterizing Brain-Cardiovascular Aging Using Multiorgan Imaging and Machine Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience Feb 19, 2025
The structure and function of the brain and cardiovascular system change over the lifespan. In this study, we aim to establish the extent to which age-related changes in these two vital organs are linked. Utilizing normative models and data from the ...
Machine Learning Neuroimaging Brain Cardiovascular System Female Humans Middle Aged Aged Magnetic Resonance Imaging Male Aged, 80 and over Heart Aging Adult
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Machine Learning Approaches to Prognostication in Traumatic Brain Injury.

Current neurology and neuroscience reports Feb 19, 2025
PURPOSE OF REVIEW: This review investigates the use of machine learning (ML) in prognosticating outcomes for traumatic brain injury (TBI). It underscores the benefits of ML models in processing and integrating complex, multimodal data-including clini...
Neuroimaging Humans Machine Learning Prognosis Brain Injuries, Traumatic
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A systematic literature review of machine learning techniques for the detection of attention-deficit/hyperactivity disorder using MRI and/or EEG data.

Neuroscience Feb 18, 2025
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition common in teenagers across the globe. Neuroimaging and Machine Learning (ML) advancements have revolutionized its diagnosis and treatment approaches. Although, the rese...
Neuroimaging Attention Deficit Disorder with Hyperactivity Magnetic Resonance Imaging Electroencephalography Humans Machine Learning Brain
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Boostering diagnosis of frontotemporal lobar degeneration with AI-driven neuroimaging - A systematic review and meta-analysis.

NeuroImage. Clinical Feb 17, 2025
BACKGROUND AND OBJECTIVES: Frontotemporal lobar degeneration (FTLD) as the second most common dementia encompasses a range of syndromes and often shows overlapping symptoms with other subtypes or neurodegenerative diseases, which poses a significant ...
Machine Learning Humans Neuroimaging Artificial Intelligence Frontotemporal Lobar Degeneration
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Prediction of cognitive conversion within the Alzheimer's disease continuum using deep learning.

Alzheimer's research & therapy Feb 13, 2025
BACKGROUND: Early diagnosis and accurate prognosis of cognitive decline in Alzheimer's disease (AD) is important to timely assignment to optimal treatment modes. We aimed to develop a deep learning model to predict cognitive conversion to guide re-as...
Deep Learning Cognitive Dysfunction Cohort Studies Male Disease Progression Neuropsychological Tests Longitudinal Studies Alzheimer Disease Neuroimaging Humans Prognosis Female Aged Aged, 80 and over
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Evaluating normative representation learning in generative AI for robust anomaly detection in brain imaging.

Nature communications Feb 13, 2025
Normative representation learning focuses on understanding the typical anatomical distributions from large datasets of medical scans from healthy individuals. Generative Artificial Intelligence (AI) leverages this attribute to synthesize images that ...
Humans Artificial Intelligence Image Processing, Computer-Assisted Algorithms Magnetic Resonance Imaging Brain Neuroimaging
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Neuradicon: Operational representation learning of neuroimaging reports.

Computer methods and programs in biomedicine Feb 12, 2025
BACKGROUND AND OBJECTIVE: Radiological reports typically summarize the content and interpretation of imaging studies in unstructured form that precludes quantitative analysis. This limits the monitoring of radiological services to throughput undiffer...
Neuroimaging Machine Learning Algorithms Natural Language Processing Humans
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