[HTML][HTML] On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
[HTML][HTML] Tumor-associated prognostic factors extractable from chest CT scans in patients with lung cancer
Accurately predicting the prognosis of patients with lung cancer before or at the time of
treatment would offer clinicians an opportunity to tailor management plans more precisely to …
treatment would offer clinicians an opportunity to tailor management plans more precisely to …
[HTML][HTML] Graph Neural Networks in Cancer and Oncology Research: Emerging and Future Trends
G Gogoshin, AS Rodin - Cancers, 2023 - mdpi.com
Simple Summary Graph Neural Networks are emerging as a powerful tool for structured data
analysis, and predictive modeling in massive multimodal datasets. In this review, we survey …
analysis, and predictive modeling in massive multimodal datasets. In this review, we survey …
GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification
Informative sample selection in an active learning (AL) setting helps a machine learning
system attain optimum performance with minimum labeled samples, thus reducing …
system attain optimum performance with minimum labeled samples, thus reducing …
[HTML][HTML] Multiside graph neural network-based attention for local co-occurrence features fusion in lung nodule classification
Early diagnosis of lung cancer is critical as it can save people's lives. Long-range
dependencies within volumetric medical images are essential attributes for accurate lung …
dependencies within volumetric medical images are essential attributes for accurate lung …
SM-GRSNet: sparse mapping-based graph representation segmentation network for honeycomb lung lesion
Y Zhang, XF Feng, Y Dong, Y Chen… - Physics in Medicine …, 2024 - iopscience.iop.org
Abstract Abstract: Objective: Honeycomb lung is a rare but severe disease characterized by
honeycomb-like imaging features and distinct radiological characteristics. Therefore, this …
honeycomb-like imaging features and distinct radiological characteristics. Therefore, this …