AI Medical Compendium Topic:
Alzheimer Disease

Clear Filters Showing 571 to 580 of 897 articles

Multi-task exclusive relationship learning for alzheimer's disease progression prediction with longitudinal data.

Medical image analysis
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive impairment of memory and other cognitive functions. Currently, many multi-task learning approaches have been proposed to predict the disease progression at the earl...

RNN-based longitudinal analysis for diagnosis of Alzheimer's disease.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and other mental functions. Magnetic resonance images (MRI) have been widely used as an important imaging modality of brain for AD diagnosis ...

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...

Training recurrent neural networks robust to incomplete data: Application to Alzheimer's disease progression modeling.

Medical image analysis
Disease progression modeling (DPM) using longitudinal data is a challenging machine learning task. Existing DPM algorithms neglect temporal dependencies among measurements, make parametric assumptions about biomarker trajectories, do not model multip...

Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI.

IEEE transactions on pattern analysis and machine intelligence
Structural magnetic resonance imaging (sMRI) has been widely used for computer-aided diagnosis of neurodegenerative disorders, e.g., Alzheimer's disease (AD), due to its sensitivity to morphological changes caused by brain atrophy. Recently, a few de...

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...

Probiotic and selenium co-supplementation, and the effects on clinical, metabolic and genetic status in Alzheimer's disease: A randomized, double-blind, controlled trial.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND AND AIMS: Combined probiotic and selenium supplementation may improve Alzheimer's disease (AD) by correcting metabolic abnormalities, and attenuating inflammation and oxidative stress. This study aimed to determine the effects of probiotic...

Seasonal Variation in Essential Oils Composition and the Biological and Pharmaceutical Protective Effects of Leaves Grown in Tunisia.

BioMed research international
This research assessed the seasonal variation of the chemical composition and antibacterial and anticholinesterase activities of essential oils extracted from leaves. The leaves organic fractions were also investigated for their biological activitie...