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 …
[HTML][HTML] A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta …
Background Deep learning offers considerable promise for medical diagnostics. We aimed
to evaluate the diagnostic accuracy of deep learning algorithms versus health-care …
to evaluate the diagnostic accuracy of deep learning algorithms versus health-care …
Med3d: Transfer learning for 3d medical image analysis
The performance on deep learning is significantly affected by volume of training data.
Models pre-trained from massive dataset such as ImageNet become a powerful weapon for …
Models pre-trained from massive dataset such as ImageNet become a powerful weapon for …
Modeling point clouds with self-attention and gumbel subset sampling
Geometric deep learning is increasingly important thanks to the popularity of 3D sensors.
Inspired by the recent advances in NLP domain, the self-attention transformer is introduced …
Inspired by the recent advances in NLP domain, the self-attention transformer is introduced …
[HTML][HTML] Early lung cancer diagnostic biomarker discovery by machine learning methods
Early diagnosis has been proved to improve survival rate of lung cancer patients. The
availability of blood-based screening could increase early lung cancer patient uptake. Our …
availability of blood-based screening could increase early lung cancer patient uptake. Our …
Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet
Background Diagnosis of rib fractures plays an important role in identifying trauma severity.
However, quickly and precisely identifying the rib fractures in a large number of CT images …
However, quickly and precisely identifying the rib fractures in a large number of CT images …
Variational few-shot learning
We propose a variational Bayesian framework for enhancing few-shot learning performance.
This idea is motivated by the fact that single point based metric learning approaches are …
This idea is motivated by the fact that single point based metric learning approaches are …
Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis
Q Pei, Y Luo, Y Chen, J Li, D Xie, T Ye - Clinical Chemistry and …, 2022 - degruyter.com
Artificial intelligence (AI) is a branch of computer science that includes research in robotics,
language recognition, image recognition, natural language processing, and expert systems …
language recognition, image recognition, natural language processing, and expert systems …
Artificial intelligence in pulmonary medicine: computer vision, predictive model and COVID-19
D Khemasuwan, JS Sorensen… - European respiratory …, 2020 - Eur Respiratory Soc
Artificial intelligence (AI) is transforming healthcare delivery. The digital revolution in
medicine and healthcare information is prompting a staggering growth of data intertwined …
medicine and healthcare information is prompting a staggering growth of data intertwined …
[HTML][HTML] Machine learning in clinical decision making
Machine learning is increasingly integrated into clinical practice, with applications ranging
from pre-clinical data processing, bedside diagnosis assistance, patient stratification …
from pre-clinical data processing, bedside diagnosis assistance, patient stratification …