AIMC Topic: Alzheimer Disease
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Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Jun 25, 2024
INTRODUCTION: Identification of individuals with mild cognitive impairment (MCI) who are at risk of developing Alzheimer's disease (AD) is crucial for early intervention and selection of clinical trials.
Siamese Graph Convolutional Network quantifies increasing structure-function discrepancy over the cognitive decline continuum.
Computer methods and programs in biomedicine
Jun 22, 2024
BACKGROUND AND OBJECTIVE: Alzheimer's disease dementia (ADD) is well known to induce alterations in both structural and functional brain connectivity. However, reported changes in connectivity are mostly limited to global/local network features, whic...
Deep Ensemble learning and quantum machine learning approach for Alzheimer's disease detection.
Scientific reports
Jun 20, 2024
Alzheimer disease (AD) is among the most chronic neurodegenerative diseases that threaten global public health. The prevalence of Alzheimer disease and consequently the increased risk of spread all over the world pose a vital threat to human safekeep...
Machine learning of dissection photographs and surface scanning for quantitative 3D neuropathology.
eLife
Jun 19, 2024
We present open-source tools for three-dimensional (3D) analysis of photographs of dissected slices of human brains, which are routinely acquired in brain banks but seldom used for quantitative analysis. Our tools can: (1) 3D reconstruct a volume fro...
Bio-inspired deep learning-personalized ensemble Alzheimer's diagnosis model for mental well-being.
SLAS technology
Jun 18, 2024
Most classification models for Alzheimer's Diagnosis (AD) do not have specific strategies for individual input samples, leading to the problem of easily overlooking personalized differences between samples. This research introduces a customized dynam...
sMRI-ADNet: an interpretable deep learning framework integrating Euclidean-graph representations of Alzheimer's disease solely from structural MRI.
Magma (New York, N.Y.)
Jun 13, 2024
OBJECTIVE: To establish a multi-dimensional representation solely on structural MRI (sMRI) for early diagnosis of AD.
Visualization of incrementally learned projection trajectories for longitudinal data.
Scientific reports
Jun 12, 2024
Longitudinal studies that continuously generate data enable the capture of temporal variations in experimentally observed parameters, facilitating the interpretation of results in a time-aware manner. We propose IL-VIS (incrementally learned visualiz...
Individual Prediction of Electric Field Induced by Deep-Brain Magnetic Stimulation With CNN-Transformer.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jun 12, 2024
Deep-brain Magnetic Stimulation (DMS) can improve the symptoms caused by Alzheimer's disease by inducing rhythmic electric field in the deep brain, and the induced electric field is rhythm-dependent. However, calculating the induced electric field re...
A deep learning model for generating [F]FDG PET Images from early-phase [F]Florbetapir and [F]Flutemetamol PET images.
European journal of nuclear medicine and molecular imaging
Jun 11, 2024
INTRODUCTION: Amyloid-β (Aβ) plaques is a significant hallmark of Alzheimer's disease (AD), detectable via amyloid-PET imaging. The Fluorine-18-Fluorodeoxyglucose ([F]FDG) PET scan tracks cerebral glucose metabolism, correlated with synaptic dysfunct...
LCADNet: a novel light CNN architecture for EEG-based Alzheimer disease detection.
Physical and engineering sciences in medicine
Jun 11, 2024
Alzheimer's disease (AD) is a progressive and incurable neurologi-cal disorder with a rising mortality rate, worsened by error-prone, time-intensive, and expensive clinical diagnosis methods. Automatic AD detection methods using hand-crafted Electroe...
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