Vision Transformers in medical computer vision—A contemplative retrospection
Abstract Vision Transformers (ViTs), with the magnificent potential to unravel the information
contained within images, have evolved as one of the most contemporary and dominant …
contained within images, have evolved as one of the most contemporary and dominant …
Demystifying supervised learning in healthcare 4.0: A new reality of transforming diagnostic medicine
The global healthcare sector continues to grow rapidly and is reflected as one of the fastest-
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …
Challenges of implementing computer-aided diagnostic models for neuroimages in a clinical setting
Advances in artificial intelligence have cultivated a strong interest in developing and
validating the clinical utilities of computer-aided diagnostic models. Machine learning for …
validating the clinical utilities of computer-aided diagnostic models. Machine learning for …
[HTML][HTML] Ensemble learning using traditional machine learning and deep neural network for diagnosis of Alzheimer's disease
In recent years, Alzheimer's disease (AD) diagnosis using neuroimaging and deep learning
has drawn great research attention. However, due to the scarcity of training neuroimaging …
has drawn great research attention. However, due to the scarcity of training neuroimaging …
Interpretable machine learning for dementia: a systematic review
Introduction Machine learning research into automated dementia diagnosis is becoming
increasingly popular but so far has had limited clinical impact. A key challenge is building …
increasingly popular but so far has had limited clinical impact. A key challenge is building …
Artificial intelligence-based diagnosis of Alzheimer's disease with brain MRI images
Z Yao, H Wang, W Yan, Z Wang, W Zhang… - European Journal of …, 2023 - Elsevier
Alzheimer's disease, a primary neurodegenerative condition, predominantly impacts the
elderly and pre-elderly population. This progressive neurological disorder is characterized …
elderly and pre-elderly population. This progressive neurological disorder is characterized …
Multimodal transformer network for incomplete image generation and diagnosis of Alzheimer's disease
Multimodal images such as magnetic resonance imaging (MRI) and positron emission
tomography (PET) could provide complementary information about the brain and have been …
tomography (PET) could provide complementary information about the brain and have been …
Short-axis PET image quality improvement based on a uEXPLORER total-body PET system through deep learning
Purpose The axial field of view (AFOV) of a positron emission tomography (PET) scanner
greatly affects the quality of PET images. Although a total-body PET scanner (uEXPLORER) …
greatly affects the quality of PET images. Although a total-body PET scanner (uEXPLORER) …
Application of deep learning for prediction of alzheimer's disease in PET/MR imaging
Y Zhao, Q Guo, Y Zhang, J Zheng, Y Yang, X Du… - Bioengineering, 2023 - mdpi.com
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects millions of
people worldwide. Positron emission tomography/magnetic resonance (PET/MR) imaging is …
people worldwide. Positron emission tomography/magnetic resonance (PET/MR) imaging is …
Deep learning aided neuroimaging and brain regulation
Currently, deep learning aided medical imaging is becoming the hot spot of AI frontier
application and the future development trend of precision neuroscience. This review aimed …
application and the future development trend of precision neuroscience. This review aimed …