AI Medical Compendium Topic:
Alzheimer Disease

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Early diagnosis of Alzheimer's disease based on deep learning: A systematic review.

Computers in biology and medicine
BACKGROUND: The improvement of health indicators and life expectancy, especially in developed countries, has led to population growth and increased age-related diseases, including Alzheimer's disease (AD). Thus, the early detection of AD is valuable ...

Deep learning-based brain age prediction in normal aging and dementia.

Nature aging
Brain aging is accompanied by patterns of functional and structural change. Alzheimer's disease (AD), a representative neurodegenerative disease, has been linked to accelerated brain aging. Here, we developed a deep learning-based brain age predictio...

Deep-Learning-Assisted Stratification of Amyloid Beta Mutants Using Drying Droplet Patterns.

Advanced materials (Deerfield Beach, Fla.)
The development of simple and accurate methods to predict mutations in proteins remains an unsolved challenge in modern biochemistry. It is discovered that critical information about primary and secondary peptide structures can be inferred from the s...

Brain network connectivity feature extraction using deep learning for Alzheimer's disease classification.

Neuroscience letters
Early diagnosis and therapeutic intervention for Alzheimer's disease (AD) is currently the only viable option for improving clinical outcomes. Combining structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imag...

Dietary administration of D-chiro-inositol attenuates sex-specific metabolic imbalances in the 5xFAD mouse model of Alzheimer's disease.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
Increasing evidence shows that hypothalamic dysfunction, insulin resistance, and weight loss precede and progress along with the cognitive decline in sporadic Alzheimer's Disease (AD) with sex differences. This study aimed to determine the effect of ...

A Single Model Deep Learning Approach for Alzheimer's Disease Diagnosis.

Neuroscience
Early and accurate diagnosis of Alzheimer's disease (AD) and its prodromal period mild cognitive impairment (MCI) is essential for the delayed disease progression and the improved quality of patients' life. The emerging computer-aided diagnostic meth...

The impact of transfer learning on 3D deep learning convolutional neural network segmentation of the hippocampus in mild cognitive impairment and Alzheimer disease subjects.

Human brain mapping
Research on segmentation of the hippocampus in magnetic resonance images through deep learning convolutional neural networks (CNNs) shows promising results, suggesting that these methods can identify small structural abnormalities of the hippocampus,...

A deep learning MRI approach outperforms other biomarkers of prodromal Alzheimer's disease.

Alzheimer's research & therapy
BACKGROUND: The three core pathologies of Alzheimer's disease (AD) are amyloid pathology, tau pathology, and neurodegeneration. Biomarkers exist for each. Neurodegeneration is often detected by neuroimaging, and we hypothesized that a voxel-based dee...

Deep learning for the dynamic prediction of multivariate longitudinal and survival data.

Statistics in medicine
The joint model for longitudinal and survival data improves time-to-event predictions by including longitudinal outcome variables in addition to baseline covariates. However, in practice, joint models may be limited by parametric assumptions in both ...

Improving Alzheimer's Disease Detection for Speech Based on Feature Purification Network.

Frontiers in public health
Alzheimer's disease (AD) is a neurodegenerative disease involving the decline of cognitive ability with illness progresses. At present, the diagnosis of AD mainly depends on the interviews between patients and doctors, which is slow, expensive, and s...