Each study has a usefulness score out of 100 (rubric version 4.0). Tap a score to see what makes it up.
Highest usefulness score first. Studies without a score come last.
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Research supporting cognitive reserve theory suggests that engaging in a variety of cognitive, social, and physical activities may serve as protective factors against age-related changes in mental functioning, especially if the activities are cognitively engaging.
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41/100
We have entered an era of a steep increase in the absolute and relative number of older people.
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We found no significant differences between the groups in age, sex, education, or cognitive level, but bilinguals showed higher FC than monolinguals between the posterior part of the superior temporal gyrus and the precuneus, positively correlated with Mini-Mental State Examination scores, and higher fALFF in the thalamus bilaterally.
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Alzheimer's disease (AD) is the most common type of dementia, and depression is a risk factor for developing AD.
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The data show that dementia research is exponentially developing following the evolution of widespread use of computer science.
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Evidence from epidemiological studies on the general population suggests that midlife cardiovascular disease (CVD) and/or metabolic syndrome (MetS) are associated with an increased risk of cognitive impairment and dementia later in life.
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The annual cost of care per patient with mild to moderate and severe major MCD was INR 78288 and INR 167808, respectively.
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Compared to healthy controls, patients with FTD showed glucose hypometabolism in bilateral frontal and temporal brain areas whereas cognition was only associated with deteriorated glucose metabolism in the left temporal lobe.
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Cognitive reserve (CR) is known to reduce or even protect against the negative effects of aging on cognitive functioning.
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The proposed hi-GCN method performs the graph embedding learning from a hierarchical perspective while considering the structure in individual brain network and the subject's correlation in the global population network, which can capture the most essential embedding features to improve the classification performance of disease diagnosis.
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Studies of resting-state functional connectivity MRI in Alzheimer's disease suggest that disease stage plays a role in functional changes of the default mode network.
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41/100
Mild cognitive impairment (MCI), an identified prodromal stage of Alzheimer's Disease (AD), often evades detection in the early stages of the condition, when existing diagnostic methods are employed in the clinical setting.
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Apathy severity was significantly associated with cortical thinning of the lateral parts of the right sided frontal, temporal and parietal lobes.
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The positive results pave the way for the deployment of the system to a nonsupervised environment, thus representing a potential efficacious and ecological solution to support clinicians in the identification of early signs of cognitive decline.
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The digitalized complex figure test evaluated copying performance quantitatively and further elucidated the patients' ongoing process during copying.
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BvFTD shows significant symptomatic overlap with non-degenerative primary psychiatric disorders including major depressive disorder, bipolar disorder, schizophrenia, obsessive-compulsive disorder, autism spectrum disorders and even personality disorders.
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The result revealed an accuracy rate of 0.84 ± 0.05, 0.79 ± 0.04, and 0.62 ± 0.06, respectively, for classifying AD vs. These results suggest that as a data-driven method, the combined CNN and EL approach can locate the most discriminable brain regions indicated by the trained ensemble model while the generalization ability of the ensemble model was maximized to successfully capture AD-related brain variations early in the disease process; it can also provide new insights into understanding the complex heterogeneity of whole-brain MRI changes in AD.
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Due to the lack of pharmacological treatment for dementia, timely detection of subjects at risk can be of seminal importance for preemptive rehabilitation interventions.
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The level of prediction error in the brain age estimation frameworks is associated with the authenticity of statistical inference on the basis of regression models.
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Deep neural networks have led to state-of-the-art results in many medical imaging tasks including Alzheimer's disease (AD) detection based on structural magnetic resonance imaging (MRI) data.
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Recent failures of potential novel therapeutics for Alzheimer's disease (AD) have prompted a drive towards clinical studies in prodromal or preclinical states.
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A World Health Organization (WHO) Feb 2018 report has recently shown that mortality rate due to brain or central nervous system (CNS) cancer is the highest in the Asian continent.
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The system uses a collected dataset of 1928 records, taken from 11 HD patients and 11 healthy persons in Lithuania, to gather statistics about examinations and presents the results as medical evaluation with prediction on the state of health.
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Structural magnetic resonance imaging (sMRI) has been widely used for computer-aided diagnosis of neurodegenerative disorders, e.g., Alzheimer's disease (AD), due to its sensitivity to morphological changes caused by brain atrophy.
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In this paper, we provide an extensive overview of machine learning techniques applied to structural magnetic resonance imaging (MRI) data to obtain clinical classifiers.
From across this topic
10 of the 1,533 studies in this topic, picked by a fixed rule (a hash of each study's address), not by score or date; each page of this list shows a different 10. The same 10 appear here every time.
- A clustering approach based on neuropsychological testing to detect early signs of probable MCI among community-dwelling older adults
- Detection of abnormal memory decline in mild cases of Alzheimer's disease using CERAD neuropsychological measures
- Comparative Analysis of Individual Graph Construction Methods from Static FDG-PET Images: an ADNI study in Alzheimer’s Disease Subjects
- Gait assessment in mild cognitive impairment and Alzheimer's disease: the effect of dual-task challenges across the cognitive spectrum
- Mediterranean diet and preserved brain structural connectivity in older subjects
- Modifiable risk factors for incident dementia and cognitive impairment: An umbrella review of evidence
- Late-life Depression and Alzheimer Disease: A Potential Synergy of the Underlying Mechanisms
- Diagnostic Utility of Multi-Domain Language Measures Across the Alzheimer Disease Continuum
- Montreal cognitive assessment: validation study for mild cognitive impairment and Alzheimer disease
- Effect of glycosylated hemoglobin on cognitive impairment related to White Matter Hyperintensity in non diabetes patients: A retrospective study