AIMC Topic: Cognitive Dysfunction

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Employing Deep-Learning Approach for the Early Detection of Mild Cognitive Impairment Transitions through the Analysis of Digital Biomarkers.

Sensors (Basel, Switzerland)
Mild cognitive impairment (MCI) is the precursor to the advanced stage of Alzheimer's disease (AD), and it is important to detect the transition to the MCI condition as early as possible. Trends in daily routines/activities provide a measurement of c...

Deep learning based diagnosis of Alzheimer's disease using FDG-PET images.

Neuroscience letters
PURPOSE: The aim of this study is to develop a deep neural network to diagnosis Alzheimer's disease and categorize the stages of the disease using FDG-PET scans. Fluorodeoxyglucose positron emission tomography (FDG-PET) is a highly effective diagnost...

c-Diadem: a constrained dual-input deep learning model to identify novel biomarkers in Alzheimer's disease.

BMC medical genomics
BACKGROUND: Alzheimer's disease (AD) is an incurable, debilitating neurodegenerative disorder. Current biomarkers for AD diagnosis require expensive neuroimaging or invasive cerebrospinal fluid sampling, thus precluding early detection. Blood-based b...

Circular-SWAT for deep learning based diagnostic classification of Alzheimer's disease: application to metabolome data.

EBioMedicine
BACKGROUND: Deep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic opti...

Distinct subtypes of spatial brain metabolism patterns in Alzheimer's disease identified by deep learning-based FDG PET clusters.

European journal of nuclear medicine and molecular imaging
PURPOSE: Alzheimer's disease (AD) is a heterogeneous disease that presents a broad spectrum of clinicopathologic profiles. To date, objective subtyping of AD independent of disease progression using brain imaging has been required. Our study aimed to...

Predicting brain age gap with radiomics and automl: A Promising approach for age-Related brain degeneration biomarkers.

Journal of neuroradiology = Journal de neuroradiologie
The Brain Age Gap (BAG), which refers to the difference between chronological age and predicted neuroimaging age, is proposed as a potential biomarker for age-related brain degeneration. However, existing brain age prediction models usually rely on a...

Improving Alzheimer Diagnoses With An Interpretable Deep Learning Framework: Including Neuropsychiatric Symptoms.

Neuroscience
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by the progressive cognitive decline. Among the various clinical symptoms, neuropsychiatric symptoms (NPS) commonly occur during the course of AD. Previous researches ha...

Using a dual-stream attention neural network to characterize mild cognitive impairment based on retinal images.

Computers in biology and medicine
Mild cognitive impairment (MCI) is a critical transitional stage between normal cognition and dementia, for which early detection is crucial for timely intervention. Retinal imaging has been shown as a promising potential biomarker for MCI. This stud...

Automating Rey Complex Figure Test scoring using a deep learning-based approach: a potential large-scale screening tool for cognitive decline.

Alzheimer's research & therapy
BACKGROUND: The Rey Complex Figure Test (RCFT) has been widely used to evaluate the neurocognitive functions in various clinical groups with a broad range of ages. However, despite its usefulness, the scoring method is as complex as the figure. Such ...

Investigating the effectiveness of socially assistive robot on depression and cognitive functions of community dwelling older adults with cognitive impairments.

Assistive technology : the official journal of RESNA
We evaluated a socially assistive robot (SAR) named Hyodol during a six-week intervention. This study enrolled 69 older adults with cognitive decline. To screen the eligibility, we have used the following three criteria, namely Korean-Mini-Mental Sta...