AIMC Topic: Brain Mapping

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Evaluation and Prediction of Early Alzheimer's Disease Using a Machine Learning-based Optimized Combination-Feature Set on Gray Matter Volume and Quantitative Susceptibility Mapping.

Current Alzheimer research Jan 1, 2020
BACKGROUND: Because Alzheimer's Disease (AD) has very complicated pattern changes, it is difficult to evaluate it with a specific factor. Recently, novel machine learning methods have been applied to solve limitations.
Humans Machine Learning Prospective Studies Male Middle Aged Cognitive Dysfunction Brain Mapping Female Aged Aged, 80 and over Cerebral Cortex Predictive Value of Tests Alzheimer Disease Gray Matter
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Convolutional Neural Network-based MR Image Analysis for Alzheimer's Disease Classification.

Current medical imaging reviews Jan 1, 2020
BACKGROUND: In this study, we used a convolutional neural network (CNN) to classify Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal control (NC) subjects based on images of the hippocampus region extracted from magnetic resonanc...
Hippocampus Case-Control Studies Cognitive Dysfunction Datasets as Topic Humans Magnetic Resonance Imaging Neural Networks, Computer Brain Mapping Alzheimer Disease Image Interpretation, Computer-Assisted
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Fusion of ULS Group Constrained High- and Low-Order Sparse Functional Connectivity Networks for MCI Classification.

Neuroinformatics Jan 1, 2020
Functional connectivity networks, derived from resting-state fMRI data, have been found as effective biomarkers for identifying mild cognitive impairment (MCI) from healthy elderly. However, the traditional functional connectivity network is essentia...
Neural Networks, Computer Algorithms Brain Humans Cognitive Dysfunction Magnetic Resonance Imaging Brain Mapping Female Least-Squares Analysis Aged Male
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Diagnosis of Autism Spectrum Disorders in Young Children Based on Resting-State Functional Magnetic Resonance Imaging Data Using Convolutional Neural Networks.

Journal of digital imaging Dec 1, 2019
Statistics show that the risk of autism spectrum disorder (ASD) is increasing in the world. Early diagnosis is most important factor in treatment of ASD. Thus far, the childhood diagnosis of ASD has been done based on clinical interviews and behavior...
Brain Mapping Image Interpretation, Computer-Assisted Neuroimaging Brain Female Male Child, Preschool Child Magnetic Resonance Imaging Humans Neural Networks, Computer Autism Spectrum Disorder
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Sign-Consistency Based Variable Importance for Machine Learning in Brain Imaging.

Neuroinformatics Oct 1, 2019
An important problem that hinders the use of supervised classification algorithms for brain imaging is that the number of variables per single subject far exceeds the number of training subjects available. Deriving multivariate measures of variable i...
Humans Machine Learning Algorithms Brain Brain Mapping Reproducibility of Results Support Vector Machine Magnetic Resonance Imaging
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Machine learning technique reveals intrinsic characteristics of schizophrenia: an alternative method.

Brain imaging and behavior Oct 1, 2019
Machine learning technique has long been utilized to assist disease diagnosis, increasing clinical physicians' confidence in their decision and expediting the process of diagnosis. In this case, machine learning technique serves as a tool for disting...
Neural Pathways Brain Female Adult Brain Mapping Temporal Lobe Male Humans Schizophrenia Brief Psychiatric Rating Scale Magnetic Resonance Imaging Machine Learning
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Machine learning transforms how microstates are sampled.

Science (New York, N.Y.) Sep 6, 2019
Deep Learning Brain Mapping Machine Learning
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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...
Female Gray Matter Dysmenorrhea Young Adult Humans Adult Surveys and Questionnaires Sensitivity and Specificity Machine Learning Magnetic Resonance Imaging Brain Brain Mapping
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Image Based Brain Segmentation: From Multi-Atlas Fusion to Deep Learning.

Current medical imaging reviews Jan 1, 2019
BACKGROUND: This review aims to identify the development of the algorithms for brain tissue and structure segmentation in MRI images.
Neuroimaging Humans Algorithms Deep Learning Brain Magnetic Resonance Imaging Brain Mapping
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Technologies to watch in 2019.

Nature Jan 1, 2019
Humans Gene Editing Animals Neural Pathways Brain Mapping Deep Learning Cryoelectron Microscopy CRISPR-Cas Systems Single-Cell Analysis Synthetic Biology Genomics
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