AI Medical Compendium Topic:
Alzheimer Disease

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Personal Precise Force Field for Intrinsically Disordered and Ordered Proteins Based on Deep Learning.

Journal of chemical information and modeling
Intrinsically disordered proteins (IDPs) are proteins without a fixed three-dimensional (3D) structure under physiological conditions and are associated with Parkinson's disease, Alzheimer's disease, cancer, cardiovascular disease, amyloidosis, diabe...

Deep learning-based speech analysis for Alzheimer's disease detection: a literature review.

Alzheimer's research & therapy
BACKGROUND: Alzheimer's disease has become one of the most common neurodegenerative diseases worldwide, which seriously affects the health of the elderly. Early detection and intervention are the most effective prevention methods currently. Compared ...

VGG-TSwinformer: Transformer-based deep learning model for early Alzheimer's disease prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Mild cognitive impairment (MCI) is a transitional state between normal aging and Alzheimer's disease (AD), and accurately predicting the progression trend of MCI is critical to the early prevention and treatment of AD. Brain...

Interpretable brain disease classification and relevance-guided deep learning.

Scientific reports
Deep neural networks are increasingly used for neurological disease classification by MRI, but the networks' decisions are not easily interpretable by humans. Heat mapping by deep Taylor decomposition revealed that (potentially misleading) image feat...

Generative adversarial network constrained multiple loss autoencoder: A deep learning-based individual atrophy detection for Alzheimer's disease and mild cognitive impairment.

Human brain mapping
Exploring individual brain atrophy patterns is of great value in precision medicine for Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, the current individual brain atrophy detection models are deficient. Here, we proposed a fr...

Zoom-In Neural Network Deep-Learning Model for Alzheimer's Disease Assessments.

Sensors (Basel, Switzerland)
Deep neural networks have been successfully applied to generate predictive patterns from medical and diagnostic data. This paper presents an approach for assessing persons with Alzheimer's disease (AD) mild cognitive impairment (MCI), compared with n...

Multi-stage classification of Alzheimer's disease from F-FDG-PET images using deep learning techniques.

Physical and engineering sciences in medicine
The study aims to implement a convolutional neural network framework that uses the 18F-FDG PET modality of brain imaging to detect multiple stages of dementia, including Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI)...

Multi-label classification of Alzheimer's disease stages from resting-state fMRI-based correlation connectivity data and deep learning.

Computers in biology and medicine
Alzheimer's disease is a neurodegenerative condition that gradually impairs cognitive abilities. Recently, various neuroimaging modalities and machine learning methods have surfaced to diagnose Alzheimer's disease. Resting-state fMRI is a neuroimagin...

Early diagnosis of Alzheimer's disease and mild cognitive impairment based on electroencephalography: From the perspective of event related potentials and deep learning.

International journal of psychophysiology : official journal of the International Organization of Psychophysiology
Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive cognitive decline, is generally prevalent in elderly people with significant disability and mortality. There is no effective treatment for AD currently, but the early...

Deep learning-based diagnosis of Alzheimer's disease using brain magnetic resonance images: an empirical study.

Scientific reports
The limited accessibility of medical specialists for Alzheimer's disease (AD) can make obtaining an accurate diagnosis in a timely manner challenging and may influence prognosis. We investigated whether VUNO Med-DeepBrain AD (DBAD) using a deep learn...