AIMC Topic: Gray Matter

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Prediction of Multiple Sclerosis Patient Disability from Structural Connectivity using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Prediction of disability progression in multiple sclerosis patients is a critical component of their management. In particular, one challenge is to identify and characterize a patient profile who may benefit of efficient treatments. However, it is no...
Brain Image Processing, Computer-Assisted Neural Networks, Computer Multiple Sclerosis Gray Matter Disability Evaluation Magnetic Resonance Imaging Humans
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Whole-brain structural magnetic resonance imaging-based classification of primary dysmenorrhea in pain-free phase: a machine learning study.

Pain Mar 1, 2019
To develop a machine learning model to investigate the discriminative power of whole-brain gray-matter (GM) images derived from primary dysmenorrhea (PDM) women and healthy controls (HCs) during the pain-free phase and further evaluate the predictive...
Humans Machine Learning Young Adult Adult Female Brain Gray Matter Brain Mapping Dysmenorrhea Surveys and Questionnaires Magnetic Resonance Imaging Sensitivity and Specificity
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Discriminative analysis of schizophrenia using support vector machine and recursive feature elimination on structural MRI images.

Medicine Jul 1, 2016
Structural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect...
White Matter Magnetic Resonance Imaging Gray Matter Schizophrenia Image Processing, Computer-Assisted Adult Support Vector Machine Female Case-Control Studies Male Sensitivity and Specificity Humans
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Using structural MRI to identify individuals at genetic risk for bipolar disorders: a 2-cohort, machine learning study.

Journal of psychiatry & neuroscience : JPN Sep 1, 2015
BACKGROUND: Brain imaging is of limited diagnostic use in psychiatry owing to clinical heterogeneity and low sensitivity/specificity of between-group neuroimaging differences. Machine learning (ML) may better translate neuroimaging to the level of in...
Gray Matter White Matter Czech Republic Magnetic Resonance Imaging Neuroimaging Support Vector Machine Temporal Lobe Prefrontal Cortex Risk Factors Parietal Lobe Genetic Predisposition to Disease Male Adult Cohort Studies Adolescent Bipolar Disorder Canada Machine Learning Young Adult Humans Female
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