[HTML][HTML] Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer's disease …

MBT Noor, NZ Zenia, MS Kaiser, SA Mamun… - Brain informatics, 2020 - Springer
Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an
important role in understanding brain functionalities and its disorders during the last couple …

[HTML][HTML] 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 …

[HTML][HTML] Early detection of Alzheimer's disease using magnetic resonance imaging: a novel approach combining convolutional neural networks and ensemble …

D Pan, A Zeng, L Jia, Y Huang, T Frizzell… - Frontiers in …, 2020 - frontiersin.org
Early detection is critical for effective management of Alzheimer's disease (AD) and
screening for mild cognitive impairment (MCI) is common practice. Among several deep …

[HTML][HTML] Analysis of features of Alzheimer's disease: Detection of early stage from functional brain changes in magnetic resonance images using a finetuned ResNet18 …

M Odusami, R Maskeliūnas, R Damaševičius… - Diagnostics, 2021 - mdpi.com
One of the first signs of Alzheimer's disease (AD) is mild cognitive impairment (MCI), in
which there are small variants of brain changes among the intermediate stages. Although …

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 …

[HTML][HTML] An intelligent system for early recognition of Alzheimer's disease using neuroimaging

M Odusami, R Maskeliūnas, R Damaševičius - Sensors, 2022 - mdpi.com
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 …

Multimodal multitask deep learning model for Alzheimer's disease progression detection based on time series data

S El-Sappagh, T Abuhmed, SMR Islam, KS Kwak - Neurocomputing, 2020 - Elsevier
Early prediction of Alzheimer's disease (AD) is crucial for delaying its progression. As a
chronic disease, ignoring the temporal dimension of AD data affects the performance of a …

Automatic detection of Alzheimer's disease progression: An efficient information fusion approach with heterogeneous ensemble classifiers

S El-Sappagh, F Ali, T Abuhmed, J Singh, JM Alonso - Neurocomputing, 2022 - Elsevier
Predicting Alzheimer's disease (AD) progression is crucial for improving the management of
this chronic disease. Usually, data from AD patients are multimodal and time series in …

[HTML][HTML] Identification of Alzheimer's disease using a convolutional neural network model based on T1-weighted magnetic resonance imaging

JB Bae, S Lee, W Jung, S Park, W Kim, H Oh, JW Han… - Scientific reports, 2020 - nature.com
The classification of Alzheimer's disease (AD) using deep learning methods has shown
promising results, but successful application in clinical settings requires a combination of …

Artificial intelligence in brain MRI analysis of Alzheimer's disease over the past 12 years: A systematic review

TO Frizzell, M Glashutter, CC Liu, A Zeng, D Pan… - Ageing Research …, 2022 - Elsevier
Introduction Multiple structural brain changes in Alzheimer's disease (AD) and mild cognitive
impairment (MCI) have been revealed on magnetic resonance imaging (MRI). There is a fast …