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Dementia

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Importance of Serum Albumin in Deep Learning-Based Prediction of Cognitive Function Data in the Aged Using a Basic Blood Test.

Advances in experimental medicine and biology
BACKGROUND: Recently, a method using deep learning has been developed to estimate the risk of developing dementia. This method uses general blood test data from routine health examinations that reveal lifestyle-related diseases, which can lead to vas...

Identification of molecular subtypes of dementia by using blood-proteins interaction-aware graph propagational network.

Briefings in bioinformatics
Plasma protein biomarkers have been considered promising tools for diagnosing dementia subtypes due to their low variability, cost-effectiveness, and minimal invasiveness in diagnostic procedures. Machine learning (ML) methods have been applied to en...

Incremental Value of Multidomain Risk Factors for Dementia Prediction: A Machine Learning Approach.

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry
OBJECTIVE: The current evidence regarding how different predictor domains contributes to predicting incident dementia remains unclear. This study aims to assess the incremental value of five predictor domains when added to a simple dementia risk pred...

Effect of a Group-Based Personal Assistive RObot (PARO) Robot Intervention on Cognitive Function, Autonomic Nervous System Function, and Mental Well-being in Older Adults with Mild Dementia: A Randomized Controlled Trial.

Journal of the American Medical Directors Association
OBJECTIVES: Personal Assistive RObot (PARO) interventions have been used to treat agitation and mood symptoms of dementia effectively. However, the effects of a PARO intervention on physiological and cognitive function are unclear. To examine the eff...

Dementia Ontology Development to Facilitate Collection of High-Quality Dementia Data.

Studies in health technology and informatics
The population of dementia patients is on the rise, as society undergoes rapid aging. This led to an expansion of dementia-related data. This study aims to develop a comprehensive dementia ontology to facilitate the collection and analysis of high-qu...

Using Natural Language Processing on Expert Panel Discussions to Gain Insights for Recruitment, Retention and Intervention Adherence for Online Social Support Interventions on a Stage II-III Clinical Trial Among Hispanic and African American Dementia Caregivers.

Studies in health technology and informatics
We applied natural language processing (NLP) to a corpus extracted from 4 hours of expert panel discussion transcripts to determine the sustainability of a Stage II-III clinical trial of online social support interventions for Hispanic and African Am...

Improved Dementia Prediction in Cerebral Small Vessel Disease Using Deep Learning-Derived Diffusion Scalar Maps From T1.

Stroke
BACKGROUND: Cerebral small vessel disease is the most common pathology underlying vascular dementia. In small vessel disease, diffusion tensor imaging is more sensitive to white matter damage and better predicts dementia risk than conventional magnet...

Artificial intelligence prediction of In-Hospital mortality in patients with dementia: A multi-center study.

International journal of medical informatics
BACKGROUND: Prediction of mortality is very important for care planning in hospitalized patients with dementia and artificial intelligence has the potential to serve as a solution; however, this issue remains unclear. Thus, this study was conducted t...

Pain Assessment for Patients with Dementia and Communication Impairment: Feasibility Study of the Usage of Artificial Intelligence-Enabled Wearables.

Sensors (Basel, Switzerland)
BACKGROUND: Recent studies on machine learning have shown the potential to provide new methods with which to assess pain through the measurement of signals associated with physiologic responses to pain detected by wearables. We conducted a prospectiv...