AIMC Topic: Cognitive Dysfunction

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New-Onset Alzheimer's Disease and Normal Subjects 100% Differentiated by P300.

American journal of Alzheimer's disease and other dementias
Previous work has suggested that evoked potential analysis might allow the detection of subjects with new-onset Alzheimer's disease, which would be useful clinically and personally. Here, it is described how subjects with new-onset Alzheimer's diseas...

The feasibility of using robotic technology to quantify sensory, motor, and cognitive impairments associated with ALS.

Amyotrophic lateral sclerosis & frontotemporal degeneration
OBJECTIVE: We used the KINARM robot to quantify impairments in cognitive and upper-limb sensorimotor performance in a cohort of people with amyotrophic lateral sclerosis (ALS). We sought to study the feasibility of using this technology for ALS resea...

Machine Learning and Data Analytics in Pervasive Health.

Methods of information in medicine
INTRODUCTION: This accompanying editorial provides a brief introduction to this focus theme, focused on "Machine Learning and Data Analytics in Pervasive Health".

A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease.

NeuroImage
Some forms of mild cognitive impairment (MCI) are the clinical precursors of Alzheimer's disease (AD), while other MCI types tend to remain stable over-time and do not progress to AD. To identify and choose effective and personalized strategies to pr...

Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks.

NeuroImage. Clinical
We built and validated a deep learning algorithm predicting the individual diagnosis of Alzheimer's disease (AD) and mild cognitive impairment who will convert to AD (c-MCI) based on a single cross-sectional brain structural MRI scan. Convolutional n...

Antemortem CSF A42/A40 ratio predicts Alzheimer's disease pathology better than A42 in rapidly progressive dementias.

Annals of clinical and translational neurology
OBJECTIVE: Despite the critical importance of pathologically confirmed samples for biomarker validation, only a few studies have correlated CSF A42 values in vivo with postmortem Alzheimer's disease (AD) pathology, while none evaluated the CSF A42/A4...

Ultra-Low-Dose F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs.

Radiology
Purpose To reduce radiotracer requirements for amyloid PET/MRI without sacrificing diagnostic quality by using deep learning methods. Materials and Methods Forty data sets from 39 patients (mean age ± standard deviation [SD], 67 years ± 8), including...

From cognitive and clinical substrates to functional profiles: Disentangling heterogeneity in schizophrenia.

Psychiatry research
The relationship between neurocognition and functioning among patients with schizophrenia is well documented. However, integrating neuropsychological, clinical and psychopathological data to better investigate functional outcome still constitutes a c...

Geoffrey: An Automated Schedule System on a Social Robot for the Intellectually Challenged.

Computational intelligence and neuroscience
The accelerated growth of the percentage of elder people and persons with brain injury-related conditions and who are intellectually challenged are some of the main concerns of the developed countries. These persons often require special cares and ev...

Novel Effective Connectivity Inference Using Ultra-Group Constrained Orthogonal Forward Regression and Elastic Multilayer Perceptron Classifier for MCI Identification.

IEEE transactions on medical imaging
Mild cognitive impairment (MCI) detection is important, such that appropriate interventions can be imposed to delay or prevent its progression to severe stages, including Alzheimer's disease (AD). Brain connectivity network inferred from the function...