AIMC Topic: Neuroimaging

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A Multi-Task Deep Feature Selection Method for Brain Imaging Genetics.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Using brain imaging quantitative traits (QTs) for identifying genetic risk factors is an important research topic in brain imaging genetics. Many efforts have been made for this task via building linear models between imaging QTs and genetic factors ...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Polymorphism, Single Nucleotide Computational Biology Linear Models Algorithms Brain Deep Learning Neuroimaging
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Generative models of MRI-derived neuroimaging features and associated dataset of 18,000 samples.

Scientific data Dec 5, 2024
Availability of large and diverse medical datasets is often challenged by privacy and data sharing restrictions. Successful application of machine learning techniques for disease diagnosis, prognosis, and precision medicine, requires large amounts of...
Young Adult Adult Male Neuroimaging Middle Aged Magnetic Resonance Imaging Brain Humans Female Aged Machine Learning Aged, 80 and over
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Deep learning analysis of fMRI data for predicting Alzheimer's Disease: A focus on convolutional neural networks and model interpretability.

PloS one Dec 4, 2024
The early detection of Alzheimer's Disease (AD) is thought to be important for effective intervention and management. Here, we explore deep learning methods for the early detection of AD. We consider both genetic risk factors and functional magnetic ...
Magnetic Resonance Imaging Humans Female Alzheimer Disease Aged, 80 and over Neural Networks, Computer Neuroimaging Male Aged Brain Deep Learning
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Portable, low-field magnetic resonance imaging for evaluation of Alzheimer's disease.

Nature communications Dec 2, 2024
Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care assessment of patients with Alzheimer's disease (AD) in settings where conventional MRI cannot. However, image quality is limited by a lower signal-to-n...
Aged Aged, 80 and over Male Cognitive Dysfunction Machine Learning Brain Female Hippocampus Neuroimaging Signal-To-Noise Ratio White Matter Image Processing, Computer-Assisted Magnetic Resonance Imaging Alzheimer Disease Humans
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Enhancement and evaluation for deep learning-based classification of volumetric neuroimaging with 3D-to-2D knowledge distillation.

Scientific reports Nov 28, 2024
The application of deep learning techniques for the analysis of neuroimaging has been increasing recently. The 3D Convolutional Neural Network (CNN) technology, which is commonly adopted to encode volumetric information, requires a large number of da...
Neural Networks, Computer Brain Humans Neuroimaging Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted
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A comprehensive neuroimaging review of the primary and metastatic brain tumors treated with immunotherapy: current status, and the application of advanced imaging approaches and artificial intelligence.

Frontiers in immunology Nov 28, 2024
Cancer immunotherapy has emerged as a novel clinical therapeutic option for a variety of solid tumors over the past decades. The application of immunotherapy in primary and metastatic brain tumors continues to grow despite limitations due to the phys...
Treatment Outcome Neuroimaging Humans Animals Artificial Intelligence Immune Checkpoint Inhibitors Brain Neoplasms Immunotherapy
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Use of Artificial Intelligence in Imaging Dementia.

Cells Nov 27, 2024
Alzheimer's disease is the most common cause of dementia in the elderly population (aged 65 years and over), followed by vascular dementia, Lewy body dementia, and rare types of neurodegenerative diseases, including frontotemporal dementia. There is ...
Humans Artificial Intelligence Alzheimer Disease Deep Learning Neuroimaging Dementia
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BPEN: Brain Posterior Evidential Network for trustworthy brain imaging analysis.

Neural networks : the official journal of the International Neural Network Society Nov 26, 2024
The application of deep learning techniques to analyze brain functional magnetic resonance imaging (fMRI) data has led to significant advancements in identifying prospective biomarkers associated with various clinical phenotypes and neurological cond...
Magnetic Resonance Imaging Alzheimer Disease Neuroimaging Uncertainty Male Deep Learning Depression Cognitive Dysfunction Brain Humans Female Neural Networks, Computer Aged
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Effective Alzheimer's disease detection using enhanced Xception blending with snapshot ensemble.

Scientific reports Nov 26, 2024
Alzheimer's disease (AD), a prevalent neurodegenerative disorder, leads to progressive dementia, which impairs decision-making, problem-solving, and communication. While there is no cure, early detection can facilitate treatments to slow its progress...
Magnetic Resonance Imaging Alzheimer Disease Neuroimaging Brain Female Aged Disease Progression Deep Learning Aged, 80 and over Male Humans Algorithms Biomarkers
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Identification and cognitive function prediction of Alzheimer's disease based on multivariate pattern analysis of hippocampal volumes.

Journal of Alzheimer's disease : JAD Nov 25, 2024
BACKGROUND: Alzheimer's disease (AD) is strongly associated with slowly progressive hippocampal atrophy. Elucidating the relationships between local morphometric changes and disease status for early diagnosis could be aided by machine learning algori...
Multivariate Analysis Neuropsychological Tests Alzheimer Disease Hippocampus Neuroimaging Aged, 80 and over Male Cognitive Dysfunction Magnetic Resonance Imaging Organ Size Cognition Support Vector Machine Humans Machine Learning Female Aged
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