A survey on deep learning and its applications

S Dong, P Wang, K Abbas - Computer Science Review, 2021 - Elsevier
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 …

[HTML][HTML] A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues

S Shamshirband, M Fathi, A Dehzangi… - Journal of Biomedical …, 2021 - Elsevier
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 …

Deep learning approach for early detection of Alzheimer's disease

HA Helaly, M Badawy, AY Haikal - Cognitive computation, 2022 - Springer
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 …

Deep learning in Alzheimer's disease: diagnostic classification and prognostic prediction using neuroimaging data

T Jo, K Nho, AJ Saykin - Frontiers in aging neuroscience, 2019 - frontiersin.org
Deep learning, a state-of-the-art machine learning approach, has shown outstanding
performance over traditional machine learning in identifying intricate structures in complex …

Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation

J Wen, E Thibeau-Sutre, M Diaz-Melo… - Medical image …, 2020 - Elsevier
Numerous machine learning (ML) approaches have been proposed for automatic
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

F Ramzan, MUG Khan, A Rehmat, S Iqbal… - Journal of medical …, 2020 - Springer
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 …

Deep learning in mining biological data

M Mahmud, MS Kaiser, TM McGinnity, A Hussain - Cognitive computation, 2021 - Springer
Recent technological advancements in data acquisition tools allowed life scientists to
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

A Mehmood, S Yang, Z Feng, M Wang, ALS Ahmad… - Neuroscience, 2021 - Elsevier
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 …

Deep learning to detect Alzheimer's disease from neuroimaging: A systematic literature review

MA Ebrahimighahnavieh, S Luo, R Chiong - Computer methods and …, 2020 - Elsevier
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 …

Applications of deep learning and reinforcement learning to biological data

M Mahmud, MS Kaiser, A Hussain… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
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 …