AIMC Topic: Magnetic Resonance Imaging

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Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.

Psychiatry research
Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to ad...

Multivariate classification of autism spectrum disorder using frequency-specific resting-state functional connectivity--A multi-center study.

Progress in neuro-psychopharmacology & biological psychiatry
BACKGROUND: Resting-state functional magnetic resonance imaging studies examining low frequency fluctuations (0.01-0.08 Hz) have revealed atypical whole brain functional connectivity patterns in adolescents with autism spectrum disorder (ASD), and th...

Proximal tibia fracture in a patient with incomplete spinal cord injury associated with robotic treadmill training.

Spinal cord
STUDY DESIGN: One case report of proximal tibia fracture in a patient with incomplete spinal cord injury (SCI) associated with robotic treadmill training.

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging.

Medical image analysis
Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that cont...

A Sensitive and Specific Neural Signature for Picture-Induced Negative Affect.

PLoS biology
Neuroimaging has identified many correlates of emotion but has not yet yielded brain representations predictive of the intensity of emotional experiences in individuals. We used machine learning to identify a sensitive and specific signature of emoti...

Multimodal data and machine learning for surgery outcome prediction in complicated cases of mesial temporal lobe epilepsy.

Computers in biology and medicine
BACKGROUND: This study sought to predict postsurgical seizure freedom from pre-operative diagnostic test results and clinical information using a rapid automated approach, based on supervised learning methods in patients with drug-resistant focal sei...

Machine learning classification of OARSI-scored human articular cartilage using magnetic resonance imaging.

Osteoarthritis and cartilage
OBJECTIVE: The purpose of this study is to evaluate the ability of machine learning to discriminate between magnetic resonance images (MRI) of normal and pathological human articular cartilage obtained under standard clinical conditions.

Cortical feature analysis and machine learning improves detection of "MRI-negative" focal cortical dysplasia.

Epilepsy & behavior : E&B
Focal cortical dysplasia (FCD) is the most common cause of pediatric epilepsy and the third most common lesion in adults with treatment-resistant epilepsy. Advances in MRI have revolutionized the diagnosis of FCD, resulting in higher success rates fo...

Development and validation of a brain maturation index using longitudinal neuroanatomical scans.

NeuroImage
BACKGROUND: Major psychiatric disorders are increasingly being conceptualized as 'neurodevelopmental', because they are associated with aberrant brain maturation. Several studies have hypothesized that a brain maturation index integrating patterns of...