Alzheimer's disease (AD) is a severe neurological illness that demolishes memory and brain functioning. This disease affects an individual's capacity to work, think, and behave. The proportion of individuals suffering from AD is rapidly increasing. I...
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...
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...
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...
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 ...
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...
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...
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 ...
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...
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 ...
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