Machine learning techniques for the diagnosis of Alzheimer's disease: A review
Alzheimer's disease is an incurable neurodegenerative disease primarily affecting the
elderly population. Efficient automated techniques are needed for early diagnosis of …
elderly population. Efficient automated techniques are needed for early diagnosis of …
Deep learning to detect Alzheimer's disease from neuroimaging: A systematic literature review
Alzheimer's Disease (AD) is one of the leading causes of death in developed countries.
From a research point of view, impressive results have been reported using computer-aided …
From a research point of view, impressive results have been reported using computer-aided …
Hierarchical fully convolutional network for joint atrophy localization and Alzheimer's disease diagnosis using structural MRI
Structural magnetic resonance imaging (sMRI) has been widely used for computer-aided
diagnosis of neurodegenerative disorders, eg, Alzheimer's disease (AD), due to its …
diagnosis of neurodegenerative disorders, eg, Alzheimer's disease (AD), due to its …
Deep learning for Alzheimer's disease diagnosis: A survey
M Khojaste-Sarakhsi, SS Haghighi… - Artificial intelligence in …, 2022 - Elsevier
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 …
Convolutional neural networks-based MRI image analysis for the Alzheimer's disease prediction from mild cognitive impairment
Mild cognitive impairment (MCI) is the prodromal stage of Alzheimer's disease (AD).
Identifying MCI subjects who are at high risk of converting to AD is crucial for effective …
Identifying MCI subjects who are at high risk of converting to AD is crucial for effective …
A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease
Some forms of mild cognitive impairment (MCI) are the clinical precursors of Alzheimer's
disease (AD), while other MCI types tend to remain stable over-time and do not progress to …
disease (AD), while other MCI types tend to remain stable over-time and do not progress to …
An intelligent system for early recognition of Alzheimer's disease using neuroimaging
Alzheimer's disease (AD) is a neurodegenerative disease that affects brain cells, and mild
cognitive impairment (MCI) has been defined as the early phase that describes the onset of …
cognitive impairment (MCI) has been defined as the early phase that describes the onset of …
Fully automatic multi‐organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks
Purpose Intensity modulated radiation therapy (IMRT) is commonly employed for treating
head and neck (H&N) cancer with uniform tumor dose and conformal critical organ sparing …
head and neck (H&N) cancer with uniform tumor dose and conformal critical organ sparing …
A survey on deep learning for neuroimaging-based brain disorder analysis
Deep learning has recently been used for the analysis of neuroimages, such as structural
magnetic resonance imaging (MRI), functional MRI, and positron emission tomography …
magnetic resonance imaging (MRI), functional MRI, and positron emission tomography …
Artificial intelligence its uses and application in pediatric dentistry: a review
S Vishwanathaiah, HN Fageeh, SB Khanagar… - Biomedicines, 2023 - mdpi.com
In the global epidemic era, oral problems significantly impact a major population of children.
The key to a child's optimal health is early diagnosis, prevention, and treatment of these …
The key to a child's optimal health is early diagnosis, prevention, and treatment of these …