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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 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 …
A survey on U-shaped networks in medical image segmentations
The U-shaped network is one of the end-to-end convolutional neural networks (CNNs). In
electron microscope segmentation of ISBI challenge 2012, the concise architecture and …
electron microscope segmentation of ISBI challenge 2012, the concise architecture and …
Classification and prediction of brain disorders using functional connectivity: promising but challenging
Brain functional imaging data, especially functional magnetic resonance imaging (fMRI)
data, have been employed to reflect functional integration of the brain. Alteration in brain …
data, have been employed to reflect functional integration of the brain. Alteration in brain …
[HTML][HTML] Efficient and low complex architecture for detection and classification of Brain Tumor using RCNN with Two Channel CNN
Abstract The Brain Tumor is one of the most serious scenarios associated with the brain
where a cluster of abnormal cells grows in an uncontrolled fashion. The field of image …
where a cluster of abnormal cells grows in an uncontrolled fashion. The field of image …
Applications of deep learning to MRI images: A survey
Deep learning provides exciting solutions in many fields, such as image analysis, natural
language processing, and expert system, and is seen as a key method for various future …
language processing, and expert system, and is seen as a key method for various future …
DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery
Deep learning-based multi-omics data integration methods have the capability to reveal the
mechanisms of cancer development, discover cancer biomarkers and identify pathogenic …
mechanisms of cancer development, discover cancer biomarkers and identify pathogenic …
[HTML][HTML] Ambient assisted living: sco** review of artificial intelligence models, domains, technology, and concerns
Background Ambient assisted living (AAL) is a common name for various artificial
intelligence (AI)—infused applications and platforms that support their users in need in …
intelligence (AI)—infused applications and platforms that support their users in need in …
Classification of autism spectrum disorder by combining brain connectivity and deep neural network classifier
Autism spectrum disorder (ASD) is a common neurodevelopmental disorder that seriously
affects communication and sociality of patients. It is crucial to accurately identify patients with …
affects communication and sociality of patients. It is crucial to accurately identify patients with …
A review on Alzheimer's disease classification from normal controls and mild cognitive impairment using structural MR images
Alzheimer's disease (AD) is an irreversible neurodegenerative brain disorder that degrades
the memory and cognitive ability in elderly people. The main reason for memory loss and …
the memory and cognitive ability in elderly people. The main reason for memory loss and …