AI Medical Compendium Journal:
NeuroImage. Clinical

Showing 91 to 100 of 104 articles

Auditory prediction errors as individual biomarkers of schizophrenia.

NeuroImage. Clinical
Schizophrenia is a complex psychiatric disorder, typically diagnosed through symptomatic evidence collected through patient interview. We aim to develop an objective biologically-based computational tool which aids diagnosis and relies on accessible ...

Predicting primary progressive aphasias with support vector machine approaches in structural MRI data.

NeuroImage. Clinical
Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, semantic variant PPA, and the logopenic variant PPA, which are characterized by distinct patterns of language difficulties and regional brain atrophy. ...

Rey's Auditory Verbal Learning Test scores can be predicted from whole brain MRI in Alzheimer's disease.

NeuroImage. Clinical
Rey's Auditory Verbal Learning Test (RAVLT) is a powerful neuropsychological tool for testing episodic memory, which is widely used for the cognitive assessment in dementia and pre-dementia conditions. Several studies have shown that an impairment in...

Metrics of brain network architecture capture the impact of disease in children with epilepsy.

NeuroImage. Clinical
BACKGROUND AND OBJECTIVE: Epilepsy is associated with alterations in the structural framework of the cerebral network. The aim of this study was to measure the potential of global metrics of network architecture derived from resting state functional ...

Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry.

NeuroImage. Clinical
This paper presents a brain T1-weighted structural magnetic resonance imaging (MRI) biomarker that combines several individual MRI biomarkers (cortical thickness measurements, volumetric measurements, hippocampal shape, and hippocampal texture). The ...

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

NeuroImage. Clinical
Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clin...

Decoding post-stroke motor function from structural brain imaging.

NeuroImage. Clinical
Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine ...

Accuracy of automated classification of major depressive disorder as a function of symptom severity.

NeuroImage. Clinical
BACKGROUND: Growing evidence documents the potential of machine learning for developing brain based diagnostic methods for major depressive disorder (MDD). As symptom severity may influence brain activity, we investigated whether the severity of MDD ...

Frequency-dependent changes in local intrinsic oscillations in chronic primary insomnia: A study of the amplitude of low-frequency fluctuations in the resting state.

NeuroImage. Clinical
New neuroimaging techniques have led to significant advancements in our understanding of cerebral mechanisms of primary insomnia. However, the neuronal low-frequency oscillation remains largely uncharacterized in chronic primary insomnia (CPI). In th...

Classification of amyloid status using machine learning with histograms of oriented 3D gradients.

NeuroImage. Clinical
Brain amyloid burden may be quantitatively assessed from positron emission tomography imaging using standardised uptake value ratios. Using these ratios as an adjunct to visual image assessment has been shown to improve inter-reader reliability, howe...