IEEE journal of biomedical and health informatics
May 13, 2015
Computer-aided diagnosis of dementia using a support vector machine (SVM) can be improved with feature selection. The relevance of individual features can be quantified from the SVM weights as a significance map (p-map). Although these p-maps previou...
Preterm birth has been shown to induce an altered developmental trajectory of brain structure and function. With the aid support vector machine (SVM) classification methods we aimed to investigate whether MRI data, collected in adolescence, could be ...
International journal of geriatric psychiatry
Feb 17, 2015
OBJECTIVE: Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate ...
Cerebral cortex (New York, N.Y. : 1991)
May 16, 2014
Conventional mass-univariate analyses have been previously used to test for group differences in neural signals. However, machine learning algorithms represent a multivariate decoding approach that may help to identify neuroimaging patterns associate...
Alzheimer's & dementia : the journal of the Alzheimer's Association
May 1, 2025
INTRODUCTION: Alzheimer's disease (AD), a leading cause of dementia, requires early detection for effective intervention. This study employs AI to analyze multimodal datasets, including clinical, biomarker, and neuroimaging data, using hybrid deep le...
White matter hyperintensities (WMH) are neuroimaging markers linked to an elevated risk of cognitive decline. WMH severity is typically assessed via visual rating scales and through volumetric segmentation. While visual rating scales are commonly use...
Background Portable low-field-strength (64-mT) MRI scanners show promise for increasing access to neuroimaging for clinical and research purposes; however, these devices produce lower-quality images than conventional high-field-strength scanners. Pur...
Background Acute ischemic stroke (AIS) is a major cause of morbidity and mortality, requiring swift and precise clinical decisions based on neuroimaging. Recent advances in deep learning-based computer vision and language artificial intelligence (AI)...
Given the relationship between hippocampal atrophy and cognitive impairment in various pathological conditions, hippocampus segmentation from MRI is an important task in neuroimaging. Manual segmentation, though considered the gold standard, is time-...