AIMC Topic: Brain Diseases
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Hierarchical Graph Convolutional Network Built by Multiscale Atlases for Brain Disorder Diagnosis Using Functional Connectivity.
IEEE transactions on neural networks and learning systems
Oct 29, 2024
Functional connectivity network (FCN) data from functional magnetic resonance imaging (fMRI) is increasingly used for the diagnosis of brain disorders. However, state-of-the-art studies used to build the FCN using a single brain parcellation atlas at...
Knowledge-driven multi-graph convolutional network for brain network analysis and potential biomarker discovery.
Medical image analysis
Oct 9, 2024
In brain network analysis, individual-level data can provide biological features of individuals, while population-level data can provide demographic information of populations. However, existing methods mostly utilize either individual- or population...
Assessing the Performance of Artificial Intelligence Models: Insights from the American Society of Functional Neuroradiology Artificial Intelligence Competition.
AJNR. American journal of neuroradiology
Sep 9, 2024
BACKGROUND AND PURPOSE: Artificial intelligence models in radiology are frequently developed and validated using data sets from a single institution and are rarely tested on independent, external data sets, raising questions about their generalizabil...
Beyond the Conventional Structural MRI: Clinical Application of Deep Learning Image Reconstruction and Synthetic MRI of the Brain.
Investigative radiology
Aug 20, 2024
Recent technological advancements have revolutionized routine brain magnetic resonance imaging (MRI) sequences, offering enhanced diagnostic capabilities in intracranial disease evaluation. This review explores 2 pivotal breakthrough areas: deep lear...
Adaptive node feature extraction in graph-based neural networks for brain diseases diagnosis using self-supervised learning.
NeuroImage
Jul 24, 2024
Electroencephalography (EEG) has demonstrated significant value in diagnosing brain diseases. In particular, brain networks have gained prominence as they offer additional valuable insights by establishing connections between EEG signal channels. Whi...
Evaluation of 3D T1-weighted spoiled gradient echo MR image quality using artificial intelligence image reconstruction techniques in the pediatric brain.
Neuroradiology
Jul 5, 2024
PURPOSE: To assess image quality and diagnostic confidence of 3D T1-weighted spoiled gradient echo (SPGR) MRI using artificial intelligence (AI) reconstruction.
Evaluation of T2W FLAIR MR image quality using artificial intelligence image reconstruction techniques in the pediatric brain.
Pediatric radiology
Jun 18, 2024
BACKGROUND: Artificial intelligence (AI) reconstruction techniques have the potential to improve image quality and decrease imaging time. However, these techniques must be assessed for safe and effective use in clinical practice.
Perineuronal Net Microscopy: From Brain Pathology to Artificial Intelligence.
International journal of molecular sciences
Apr 11, 2024
Perineuronal nets (PNN) are a special highly structured type of extracellular matrix encapsulating synapses on large populations of CNS neurons. PNN undergo structural changes in schizophrenia, epilepsy, Alzheimer's disease, stroke, post-traumatic co...
Connectional-style-guided contextual representation learning for brain disease diagnosis.
Neural networks : the official journal of the International Neural Network Society
Apr 7, 2024
Structural magnetic resonance imaging (sMRI) has shown great clinical value and has been widely used in deep learning (DL) based computer-aided brain disease diagnosis. Previous DL-based approaches focused on local shapes and textures in brain sMRI t...
Clinical performance of automated machine learning: A systematic review.
Annals of the Academy of Medicine, Singapore
Mar 27, 2024
INTRODUCTION: Automated machine learning (autoML) removes technical and technological barriers to building artificial intelligence models. We aimed to summarise the clinical applications of autoML, assess the capabilities of utilised platforms, evalu...
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