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A survey on deep learning and its applications
Deep learning, a branch of machine learning, is a frontier for artificial intelligence, aiming to
be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary …
be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary …
[HTML][HTML] A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues
In the last few years, the application of Machine Learning approaches like Deep Neural
Network (DNN) models have become more attractive in the healthcare system given the …
Network (DNN) models have become more attractive in the healthcare system given the …
Deep learning approach for early detection of Alzheimer's disease
Alzheimer's disease (AD) is a chronic, irreversible brain disorder, no effective cure for it till
now. However, available medicines can delay its progress. Therefore, the early detection of …
now. However, available medicines can delay its progress. Therefore, the early detection of …
Deep learning in Alzheimer's disease: diagnostic classification and prognostic prediction using neuroimaging data
Deep learning, a state-of-the-art machine learning approach, has shown outstanding
performance over traditional machine learning in identifying intricate structures in complex …
performance over traditional machine learning in identifying intricate structures in complex …
Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation
Numerous machine learning (ML) approaches have been proposed for automatic
classification of Alzheimer's disease (AD) from brain imaging data. In particular, over 30 …
classification of Alzheimer's disease (AD) from brain imaging data. In particular, over 30 …
A deep learning approach for automated diagnosis and multi-class classification of Alzheimer's disease stages using resting-state fMRI and residual neural networks
Alzheimer's disease (AD) is an incurable neurodegenerative disorder accounting for 70%–
80% dementia cases worldwide. Although, research on AD has increased in recent years …
80% dementia cases worldwide. Although, research on AD has increased in recent years …
Deep learning in mining biological data
Recent technological advancements in data acquisition tools allowed life scientists to
acquire multimodal data from different biological application domains. Categorized in three …
acquire multimodal data from different biological application domains. Categorized in three …
A transfer learning approach for early diagnosis of Alzheimer's disease on MRI images
Mild cognitive impairment (MCI) detection using magnetic resonance image (MRI), plays a
crucial role in the treatment of dementia disease at an early stage. Deep learning …
crucial role in the treatment of dementia disease at an early stage. Deep learning …
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 …
Applications of deep learning and reinforcement learning to biological data
Rapid advances in hardware-based technologies during the past decades have opened up
new possibilities for life scientists to gather multimodal data in various application domains …
new possibilities for life scientists to gather multimodal data in various application domains …