AIMC Topic: Functional Neuroimaging

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Convolutional Neural Networks for Pediatric Refractory Epilepsy Classification Using Resting-State Functional Magnetic Resonance Imaging.

World neurosurgery Jan 6, 2021
OBJECTIVE: This study aims to evaluate the performance of convolutional neural networks (CNNs) trained with resting-state functional magnetic resonance imaging (rfMRI) latency data in the classification of patients with pediatric epilepsy from health...
Humans Neural Networks, Computer Brain Female Male Magnetic Resonance Imaging Area Under Curve Rest Neural Pathways Drug Resistant Epilepsy Case-Control Studies Functional Neuroimaging Adolescent Child ROC Curve
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Machine learning-based multimodal prediction of language outcomes in chronic aphasia.

Human brain mapping Dec 30, 2020
Recent studies have combined multiple neuroimaging modalities to gain further understanding of the neurobiological substrates of aphasia. Following this line of work, the current study uses machine learning approaches to predict aphasia severity and ...
Cerebrovascular Circulation Diffusion Tensor Imaging Language Tests Aphasia Severity of Illness Index Aged Functional Neuroimaging Aged, 80 and over Support Vector Machine Adult Magnetic Resonance Imaging Humans Male Multimodal Imaging Female Middle Aged Chronic Disease Stroke Outcome Assessment, Health Care Neuroimaging
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Broad Learning Enhanced H-MRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus.

Computational and mathematical methods in medicine Nov 22, 2020
In this paper, we explore the potential of using the multivoxel proton magnetic resonance spectroscopy (H-MRS) to diagnose neuropsychiatric systemic lupus erythematosus (NPSLE) with the assistance of a support vector machine broad learning system (BL...
Computational Biology Adult Humans Proton Magnetic Resonance Spectroscopy Support Vector Machine Brain Lupus Vasculitis, Central Nervous System Magnetic Resonance Imaging Male Early Diagnosis Case-Control Studies Diagnosis, Computer-Assisted Functional Neuroimaging Retrospective Studies Female
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Comparing machine and deep learning-based algorithms for prediction of clinical improvement in psychosis with functional magnetic resonance imaging.

Human brain mapping Nov 13, 2020
Previous work using logistic regression suggests that cognitive control-related frontoparietal activation in early psychosis can predict symptomatic improvement after 1 year of coordinated specialty care with 66% accuracy. Here, we evaluated the abil...
Female Young Adult Adult Male Deep Learning Humans Machine Learning Follow-Up Studies Magnetic Resonance Imaging Schizophrenia Outcome Assessment, Health Care Psychomotor Performance Functional Neuroimaging Adolescent Bipolar Disorder Support Vector Machine Dorsolateral Prefrontal Cortex Executive Function
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Designing individual-specific and trial-specific models to accurately predict the intensity of nociceptive pain from single-trial fMRI responses.

NeuroImage Oct 27, 2020
Using machine learning to predict the intensity of pain from fMRI has attracted rapidly increasing interests. However, due to remarkable inter- and intra-individual variabilities in pain responses, the performance of existing fMRI-based pain predicti...
Humans Machine Learning Least-Squares Analysis Supervised Machine Learning Nociceptive Pain Male Functional Neuroimaging Magnetic Resonance Imaging Cluster Analysis Pain Measurement Brain Female Young Adult Adult
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Predicting brain age with complex networks: From adolescence to adulthood.

NeuroImage Oct 21, 2020
In recent years, several studies have demonstrated that machine learning and deep learning systems can be very useful to accurately predict brain age. In this work, we propose a novel approach based on complex networks using 1016 T1-weighted MRI brai...
Adolescent Development Functional Neuroimaging Adolescent Child Magnetic Resonance Imaging Child Development Male Aging Middle Aged Deep Learning Humans Neural Networks, Computer Autism Spectrum Disorder Brain Female Young Adult Adult
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Predicting memory from study-related brain activity.

Journal of neurophysiology Oct 21, 2020
To isolate brain activity that may reflect effective cognitive processes during the study phase of a memory task, cognitive neuroscientists commonly contrast brain activity during study of later-remembered versus later-forgotten items. This "subseque...
Mental Recall Recognition, Psychology Humans Machine Learning Adult Functional Neuroimaging Electroencephalography Pattern Recognition, Automated Cerebral Cortex Evoked Potentials
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Multi-dimensional predictions of psychotic symptoms via machine learning.

Human brain mapping Sep 1, 2020
The diagnostic criteria for schizophrenia comprise a diverse range of heterogeneous symptoms. As a result, individuals each present a distinct set of symptoms despite having the same overall diagnosis. Whilst previous machine learning studies have pr...
Schizophrenia Psychotic Disorders Attention Motivation Anhedonia Hallucinations Humans Auditory Perception Machine Learning Male Prognosis Middle Aged Female Functional Neuroimaging Young Adult Adolescent Adult Magnetic Resonance Imaging
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Morphological Characterization of Functional Brain Imaging by Isosurface Analysis in Parkinson's Disease.

International journal of neural systems Aug 12, 2020
Finding new biomarkers to model Parkinson's Disease (PD) is a challenge not only to help discerning between Healthy Control (HC) subjects and patients with potential PD but also as a way to measure quantitatively the loss of dopaminergic neurons main...
Support Vector Machine Humans Parkinson Disease Tomography, Emission-Computed, Single-Photon Machine Learning Databases, Factual Functional Neuroimaging
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A Comparative Analysis of Visual Encoding Models Based on Classification and Segmentation Task-Driven CNNs.

Computational and mathematical methods in medicine Aug 1, 2020
Nowadays, visual encoding models use convolution neural networks (CNNs) with outstanding performance in computer vision to simulate the process of human information processing. However, the prediction performances of encoding models will have differe...
Magnetic Resonance Imaging Models, Neurological Photic Stimulation Visual Perception Visual Cortex Humans Algorithms Databases, Factual Neural Networks, Computer Functional Neuroimaging Artificial Intelligence Image Processing, Computer-Assisted
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