Multi-channel multi-task deep learning for predicting EGFR and KRAS mutations of non-small cell lung cancer on CT images-Reference-Cited by-同舟云学术

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Multi-channel multi-task deep learning for predicting EGFR and KRAS mutations of non-small cell lung cancer on CT images

Published:2021-06 Issue:6 Volume:11 Page:2354-2375
ISSN:2223-4292
Container-title:Quantitative Imaging in Medicine and Surgery
language:
Short-container-title:Quant Imaging Med Surg

Author:

Dong Yunyun,Hou Lina,Yang Wenkai,Han Jiahao,Wang Jiawen,Qiang Yan,Zhao Juanjuan,Hou Jiaxin,Song Kai,Ma Yulan,Kazihise Ntikurako Guy Fernand,Cui Yanfen,Yang Xiaotang

Publisher

AME Publishing Company

Subject

Radiology Nuclear Medicine and imaging

Link

https://qims.amegroups.com/article/download/66279/pdf

Cited by 26 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Exploring the Use of Deep Learning Models in Predicting Genetic Mutations Associated with Non-Small Cell Lung Cancer: A Systematic Review (Preprint);2024-09-07

2. Comprehensive Potential of Artificial Intelligence for Predicting PD-L1 Expression and EGFR Mutations in Lung Cancer: A Systematic Review and Meta-Analysis;Journal of Computer Assisted Tomography;2024-08-12

3. Deep learning in pulmonary nodule detection and segmentation: a systematic review;European Radiology;2024-07-10

4. Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023;Cancer Imaging;2024-07-04

5. Predict EGFR Mutation Status on CT Images Using Texture and Contour Enhanced Masked Autoencoders;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

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