AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction
Abstract The prediction of Mild Cognitive Impairment (MCI) patients who are at higher risk
converting to Alzheimer's Disease (AD) is critical for effective intervention and patient …
converting to Alzheimer's Disease (AD) is critical for effective intervention and patient …
Transfer learning for predicting conversion from mild cognitive impairment to dementia of Alzheimer's type based on a three-dimensional convolutional neural network
Dementia of Alzheimer's type (DAT) is associated with devastating and irreversible cognitive
decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT …
decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT …
Two-stage deep learning model for Alzheimer's disease detection and prediction of the mild cognitive impairment time
Alzheimer's disease (AD) is an irreversible neurodegenerative disease characterized by
thinking, behavioral and memory impairments. Early prediction of conversion from mild …
thinking, behavioral and memory impairments. Early prediction of conversion from mild …
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 …
Multimodal ensemble model for Alzheimer's disease conversion prediction from Early Mild Cognitive Impairment subjects
M Velazquez, Y Lee - computers in Biology and Medicine, 2022 - Elsevier
Alzheimer's Disease (AD) is the most common type of dementia. Predicting the conversion to
Alzheimer's from the mild cognitive impairment (MCI) stage is a complex problem that has …
Alzheimer's from the mild cognitive impairment (MCI) stage is a complex problem that has …
Predicting conversion of mild cognitive impairments to Alzheimer's disease and exploring impact of neuroimaging
Y Shmulev, M Belyaev… - Graphs in Biomedical …, 2018 - Springer
Nowadays, a lot of scientific efforts are concentrated on the diagnosis of Alzheimers Disease
(AD) applying deep learning methods to neuroimaging data. Even for 2017, there were …
(AD) applying deep learning methods to neuroimaging data. Even for 2017, there were …
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 transformer-based multi-features fusion model for prediction of conversion in mild cognitive impairment
G Zheng, Y Zhang, Z Zhao, Y Wang, X Liu, Y Shang… - Methods, 2022 - Elsevier
Mild cognitive impairment (MCI) is usually considered the early stage of Alzheimer's disease
(AD). Therefore, the accurate identification of MCI individuals with high risk in converting to …
(AD). Therefore, the accurate identification of MCI individuals with high risk in converting to …
Transfer learning with intelligent training data selection for prediction of Alzheimer's disease
Detection of Alzheimer's disease (AD) from neuroimaging data such as MRI through
machine learning has been a subject of intense research in recent years. The recent …
machine learning has been a subject of intense research in recent years. The recent …
Predicting Alzheimer's disease progression using multi-modal deep learning approach
Alzheimer's disease (AD) is a progressive neurodegenerative condition marked by a decline
in cognitive functions with no validated disease modifying treatment. It is critical for timely …
in cognitive functions with no validated disease modifying treatment. It is critical for timely …