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
N Kesav, MG Jibukumar - Journal of King Saud University-Computer and …, 2022 - Elsevier
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 …
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 …
[HTML][HTML] Ambient assisted living: scoping 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 …
GANLDA: graph attention network for lncRNA-disease associations prediction
Increasing studies have indicated that long non-coding RNAs (lncRNAs) play important
roles in many physiological and pathological pathways. Identifying lncRNA-disease …
roles in many physiological and pathological pathways. Identifying lncRNA-disease …
Complex brain network analysis and its applications to brain disorders: a survey
It is well known that most brain disorders are complex diseases, such as Alzheimer's
disease (AD) and schizophrenia (SCZ). In general, brain regions and their interactions can …
disease (AD) and schizophrenia (SCZ). In general, brain regions and their interactions can …