Machine learning methods for predicting progression from mild cognitive impairment to Alzheimer's disease dementia: a systematic review
S Grueso, R Viejo-Sobera - Alzheimer's research & therapy, 2021 - Springer
Background An increase in lifespan in our society is a double-edged sword that entails a
growing number of patients with neurocognitive disorders, Alzheimer's disease being the …
growing number of patients with neurocognitive disorders, Alzheimer's disease being the …
Machine learning and novel biomarkers for the diagnosis of Alzheimer's disease
Background: Alzheimer's disease (AD) is a complex and severe neurodegenerative disease
that still lacks effective methods of diagnosis. The current diagnostic methods of AD rely on …
that still lacks effective methods of diagnosis. The current diagnostic methods of AD rely on …
Multi-method analysis of medical records and MRI images for early diagnosis of dementia and Alzheimer's disease based on deep learning and hybrid methods
Dementia and Alzheimer's disease are caused by neurodegeneration and poor
communication between neurons in the brain. So far, no effective medications have been …
communication between neurons in the brain. So far, no effective medications have been …
Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images …
Biomarkers for dementia of Alzheimer's type (DAT) are sought to facilitate accurate
prediction of the disease onset, ideally predating the onset of cognitive deterioration. T1 …
prediction of the disease onset, ideally predating the onset of cognitive deterioration. T1 …
Predicting the progression of mild cognitive impairment using machine learning: a systematic, quantitative and critical review
We performed a systematic review of studies focusing on the automatic prediction of the
progression of mild cognitive impairment to Alzheimer's disease (AD) dementia, and a …
progression of mild cognitive impairment to Alzheimer's disease (AD) dementia, and a …
Diffusion MRI indices and their relation to cognitive impairment in brain aging: the updated multi-protocol approach in ADNI3
Brain imaging with diffusion-weighted MRI (dMRI) is sensitive to microstructural white matter
(WM) changes associated with brain aging and neurodegeneration. In its third phase, the …
(WM) changes associated with brain aging and neurodegeneration. In its third phase, the …
Artificial intelligence for diagnostic and prognostic neuroimaging in dementia: A systematic review
Introduction Artificial intelligence (AI) and neuroimaging offer new opportunities for
diagnosis and prognosis of dementia. Methods We systematically reviewed studies …
diagnosis and prognosis of dementia. Methods We systematically reviewed studies …
Quantifying brain metabolism from FDG‐PET images into a probability of Alzheimer's dementia score
Abstract 18F‐fluorodeoxyglucose positron emission tomography (FDG‐PET) enables in‐
vivo capture of the topographic metabolism patterns in the brain. These images have shown …
vivo capture of the topographic metabolism patterns in the brain. These images have shown …
Predicting time-to-conversion for dementia of Alzheimer's type using multi-modal deep survival analysis
Abstract Dementia of Alzheimer's Type (DAT) is a complex disorder influenced by numerous
factors, and it is difficult to predict individual progression trajectory from normal or mildly …
factors, and it is difficult to predict individual progression trajectory from normal or mildly …
Machine learning based multi-modal prediction of future decline toward Alzheimer's disease: an empirical study
Alzheimer's disease (AD) is a neurodegenerative condition that progresses over decades.
Early detection of individuals at high risk of future progression toward AD is likely to be of …
Early detection of individuals at high risk of future progression toward AD is likely to be of …