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Machine learning methods for predicting progression from mild cognitive impairment to Alzheimer's disease dementia: a systematic review
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 …
Deep learning for Alzheimer's disease diagnosis: A survey
Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a
progressive decline in cognitive abilities. Since AD starts several years before the onset of …
progressive decline in cognitive abilities. Since AD starts several years before the onset of …
An evolutionary explainable deep learning approach for Alzheimer's MRI classification
Abstract Deep Neural Networks (DNN) are prominent Machine Learning (ML) algorithms
widely used, especially in medical tasks. Among them, Convolutional Neural Networks …
widely used, especially in medical tasks. Among them, Convolutional Neural Networks …
Multi-model and multi-slice ensemble learning architecture based on 2D convolutional neural networks for Alzheimer's disease diagnosis
Alzheimer's Disease (AD) is a chronic neurodegenerative disease without effective
medications or supplemental treatments. Thus, predicting AD progression is crucial for …
medications or supplemental treatments. Thus, predicting AD progression is crucial for …
[HTML][HTML] Artificial intelligence for Alzheimer's disease: promise or challenge?
Decades of experimental and clinical research have contributed to unraveling many
mechanisms in the pathogenesis of Alzheimer's disease (AD), but the puzzle is still …
mechanisms in the pathogenesis of Alzheimer's disease (AD), but the puzzle is still …
[HTML][HTML] Advancements in computer-assisted diagnosis of Alzheimer's disease: A comprehensive survey of neuroimaging methods and AI techniques for early …
Alzheimer's Disease (AD) is a brain disorder that causes the brain to shrink and eventually
causes brain cells to die. This neurological condition progressively hampers cognitive and …
causes brain cells to die. This neurological condition progressively hampers cognitive and …
[HTML][HTML] Applications of artificial intelligence to aid early detection of dementia: a sco** review on current capabilities and future directions
Abstract Background & Objective With populations aging, the number of people with
dementia worldwide is expected to triple to 152 million by 2050. Seventy percent of cases …
dementia worldwide is expected to triple to 152 million by 2050. Seventy percent of cases …
AHANet: Adaptive hybrid attention network for Alzheimer's disease classification using brain magnetic resonance imaging
Alzheimer's disease (AD) is a progressive neurological problem that causes brain atrophy
and affects the memory and thinking skills of an individual. Accurate detection of AD has …
and affects the memory and thinking skills of an individual. Accurate detection of AD has …
Vision transformers for the prediction of mild cognitive impairment to Alzheimer's disease progression using mid-sagittal sMRI
Background Alzheimer's disease (AD) is one of the most common causes of
neurodegenerative disease affecting over 50 million people worldwide. However, most AD …
neurodegenerative disease affecting over 50 million people worldwide. However, most AD …
Interpretable machine learning for dementia: a systematic review
Introduction Machine learning research into automated dementia diagnosis is becoming
increasingly popular but so far has had limited clinical impact. A key challenge is building …
increasingly popular but so far has had limited clinical impact. A key challenge is building …