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Cognitive Dysfunction

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Improving Alzheimer's Disease Detection for Speech Based on Feature Purification Network.

Frontiers in public health
Alzheimer's disease (AD) is a neurodegenerative disease involving the decline of cognitive ability with illness progresses. At present, the diagnosis of AD mainly depends on the interviews between patients and doctors, which is slow, expensive, and s...

Cognitive Impairment of Patient With Neurological Cerebrovascular Disease Using the Artificial Intelligence Technology Guided by MRI.

Frontiers in public health
This study was to explore the application of MRI based on artificial intelligence technology combined with neuropsychological assessment to the cognitive impairment of patients with neurological cerebrovascular diseases. A total of 176 patients were ...

Robots in Eldercare: How Does a Real-World Interaction with the Machine Influence the Perceptions of Older People?

Sensors (Basel, Switzerland)
(1) Background: Using autonomous social robots in selected areas of care for community-dwelling older adults is one of the promising approaches to address the problem of the widening care gap. We posed the question of whether a possibility to interac...

Deep learning identifies brain structures that predict cognition and explain heterogeneity in cognitive aging.

NeuroImage
Specific brain structures (gray matter regions and white matter tracts) play a dominant role in determining cognitive decline and explain the heterogeneity in cognitive aging. Identification of these structures is crucial for screening of older adult...

Inferring protein expression changes from mRNA in Alzheimer's dementia using deep neural networks.

Nature communications
Identifying the molecular systems and proteins that modify the progression of Alzheimer's disease and related dementias (ADRD) is central to drug target selection. However, discordance between mRNA and protein abundance, and the scarcity of proteomic...

Alteration of the corpus callosum in patients with Alzheimer's disease: Deep learning-based assessment.

PloS one
BACKGROUND: Several studies have reported changes in the corpus callosum (CC) in Alzheimer's disease. However, the involved region differed according to the study population and study group. Using deep learning technology, we ensured accurate analysi...

Subtyping of mild cognitive impairment using a deep learning model based on brain atrophy patterns.

Cell reports. Medicine
Trajectories of cognitive decline vary considerably among individuals with mild cognitive impairment (MCI). To address this heterogeneity, subtyping approaches have been developed, with the objective of identifying more homogeneous subgroups. To date...

The role of a socially assistive robot in enabling older adults with mild cognitive impairment to cope with the measures of the COVID-19 lockdown: A qualitative study.

Scandinavian journal of occupational therapy
BACKGROUND: During the COVID-19 pandemic, mandatory containment measures led to lockdowns and severely diminished social interaction, with older adults being one vulnerable group. Socially assistive robots (SARs) could prove to be an effective interv...

A deep learning framework identifies dimensional representations of Alzheimer's Disease from brain structure.

Nature communications
Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a semi-supervised deep-clustering method, which examines neuroanatomical...