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 …
progressive decline in cognitive abilities. Since AD starts several years before the onset of …
[HTML][HTML] Capsule networks–a survey
Modern day computer vision tasks requires efficient solution to problems such as image
recognition, natural language processing, object detection, object segmentation and …
recognition, natural language processing, object detection, object segmentation and …
[HTML][HTML] Deep convolutional neural network based medical image classification for disease diagnosis
Medical image classification plays an essential role in clinical treatment and teaching tasks.
However, the traditional method has reached its ceiling on performance. Moreover, by using …
However, the traditional method has reached its ceiling on performance. Moreover, by using …
Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks
Coronavirus is an epidemic that spreads very quickly. For this reason, it has very devastating
effects in many areas worldwide. It is vital to detect COVID-19 diseases as quickly as …
effects in many areas worldwide. It is vital to detect COVID-19 diseases as quickly as …
[HTML][HTML] Hybrid deep learning for detecting lung diseases from X-ray images
Lung disease is common throughout the world. These include chronic obstructive pulmonary
disease, pneumonia, asthma, tuberculosis, fibrosis, etc. Timely diagnosis of lung disease is …
disease, pneumonia, asthma, tuberculosis, fibrosis, etc. Timely diagnosis of lung disease is …
3D point capsule networks
In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process
sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule …
sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule …
[HTML][HTML] Intelligent health care: Applications of deep learning in computational medicine
S Yang, F Zhu, X Ling, Q Liu, P Zhao - Frontiers in Genetics, 2021 - frontiersin.org
With the progress of medical technology, biomedical field ushered in the era of big data,
based on which and driven by artificial intelligence technology, computational medicine has …
based on which and driven by artificial intelligence technology, computational medicine has …
Hierarchical taxonomy-aware and attentional graph capsule RCNNs for large-scale multi-label text classification
CNNs, RNNs, GCNs, and CapsNets have shown significant insights in representation
learning and are widely used in various text mining tasks such as large-scale multi-label text …
learning and are widely used in various text mining tasks such as large-scale multi-label text …
[HTML][HTML] CBIR system using Capsule Networks and 3D CNN for Alzheimer's disease diagnosis
KR Kruthika, HD Maheshappa… - Informatics in Medicine …, 2019 - Elsevier
Alzheimer's disease (AD) is an irreversible disorder of the brain related to loss of memory,
commonly seen in the elderly and aging population. Implementation of revolutionary …
commonly seen in the elderly and aging population. Implementation of revolutionary …
COVID-WideNet—A capsule network for COVID-19 detection
Ever since the outbreak of COVID-19, the entire world is grappling with panic over its rapid
spread. Consequently, it is of utmost importance to detect its presence. Timely diagnostic …
spread. Consequently, it is of utmost importance to detect its presence. Timely diagnostic …