AIMC Topic: Cognitive Dysfunction

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A Robust Deep Model for Improved Classification of AD/MCI Patients.

IEEE journal of biomedical and health informatics
Accurate classification of Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI), plays a critical role in possibly preventing progression of memory impairment and improving quality of life for AD patients. Among many rese...

Identification of a small set of plasma signalling proteins using neural network for prediction of Alzheimer's disease.

Bioinformatics (Oxford, England)
MOTIVATION: Alzheimer's disease (AD) is a dementia that gets worse with time resulting in loss of memory and cognitive functions. The life expectancy of AD patients following diagnosis is ∼7 years. In 2006, researchers estimated that 0.40% of the wor...

Predicting Prodromal Alzheimer's Disease in Subjects with Mild Cognitive Impairment Using Machine Learning Classification of Multimodal Multicenter Diffusion-Tensor and Magnetic Resonance Imaging Data.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND: Alzheimer's disease (AD) patients show early changes in white matter (WM) structural integrity. We studied the use of diffusion tensor imaging (DTI) in assessing WM alterations in the predementia stage of mild cognitive impairment (MCI).

Autonomous unobtrusive detection of mild cognitive impairment in older adults.

IEEE transactions on bio-medical engineering
The current diagnosis process of dementia is resulting in a high percentage of cases with delayed detection. To address this problem, in this paper, we explore the feasibility of autonomously detecting mild cognitive impairment (MCI) in the older adu...

Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects.

NeuroImage
Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive decline and Alzheimer's disease (AD). For the effective treatment of AD, it would be important to identify MCI patients at high risk for conversion to AD. In this s...

Manifold regularized multitask feature learning for multimodality disease classification.

Human brain mapping
Multimodality based methods have shown great advantages in classification of Alzheimer's disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint select...

The Attitudes and Perceptions of Older Adults With Mild Cognitive Impairment Toward an Assistive Robot.

Journal of applied gerontology : the official journal of the Southern Gerontological Society
The purpose of this study was to explore perceived difficulties and needs of older adults with mild cognitive impairment (MCI) and their attitudes toward an assistive robot to develop appropriate robot functionalities. Twenty subjects were recruited ...

Latent feature representation with stacked auto-encoder for AD/MCI diagnosis.

Brain structure & function
Recently, there have been great interests for computer-aided diagnosis of Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Unlike the previous methods that considered simple low-level features such as gray matter tis...

The Association Between Psychotropic Medications and Cognitive Functioning in a Real-World Cohort of 869 Individuals with Schizophrenia.

Schizophrenia bulletin
BACKGROUND: Cognitive deficits are a central feature of schizophrenia for which there are not any established pharmacological treatments. Antipsychotics are the mainstay of schizophrenia therapy but the effects of these and other psychotropic medicat...

Comparative cytokine signatures and cognitive deficits in early-onset schizophrenia and adolescent major depression: Toward refined diagnostic classification frameworks.

Journal of affective disorders
BACKGROUND: This study analyzed plasma cytokine patterns in individuals with schizophrenia (SCZ), major depressive disorder (MDD), and healthy controls, explored the link between cytokine levels and cognitive function, and created machine learning mo...