145 related articles for article (PubMed ID: 38194018)
1. Using Vision Transformer for high robustness and generalization in predicting EGFR mutation status in lung adenocarcinoma.
Weng L; Xu Y; Chen Y; Chen C; Qian Q; Pan J; Su H
Clin Transl Oncol; 2024 Jun; 26(6):1438-1445. PubMed ID: 38194018
[TBL] [Abstract][Full Text] [Related]
2. Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning.
Wang S; Shi J; Ye Z; Dong D; Yu D; Zhou M; Liu Y; Gevaert O; Wang K; Zhu Y; Zhou H; Liu Z; Tian J
Eur Respir J; 2019 Mar; 53(3):. PubMed ID: 30635290
[TBL] [Abstract][Full Text] [Related]
3. Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning.
Zhao W; Yang J; Ni B; Bi D; Sun Y; Xu M; Zhu X; Li C; Jin L; Gao P; Wang P; Hua Y; Li M
Cancer Med; 2019 Jul; 8(7):3532-3543. PubMed ID: 31074592
[TBL] [Abstract][Full Text] [Related]
4. Predicting EGFR mutation status in lung adenocarcinoma presenting as ground-glass opacity: utilizing radiomics model in clinical translation.
Cheng B; Deng H; Zhao Y; Xiong J; Liang P; Li C; Liang H; Shi J; Li J; Xiong S; Lai T; Chen Z; Wu J; Qian T; Huan W; Ng MTA; He J; Liang W
Eur Radiol; 2022 Sep; 32(9):5869-5879. PubMed ID: 35348863
[TBL] [Abstract][Full Text] [Related]
5. GMILT: A Novel Transformer Network That Can Noninvasively Predict EGFR Mutation Status.
Zhao W; Chen W; Li G; Lei D; Yang J; Chen Y; Jiang Y; Wu J; Ni B; Sun Y; Wang S; Sun Y; Li M; Liu J
IEEE Trans Neural Netw Learn Syst; 2024 Jun; 35(6):7324-7338. PubMed ID: 35862326
[TBL] [Abstract][Full Text] [Related]
6. Computed Tomography-Based Radiomics Signature: A Potential Indicator of Epidermal Growth Factor Receptor Mutation in Pulmonary Adenocarcinoma Appearing as a Subsolid Nodule.
Yang X; Dong X; Wang J; Li W; Gu Z; Gao D; Zhong N; Guan Y
Oncologist; 2019 Nov; 24(11):e1156-e1164. PubMed ID: 30936378
[TBL] [Abstract][Full Text] [Related]
7. A novel radiomic nomogram for predicting epidermal growth factor receptor mutation in peripheral lung adenocarcinoma.
Lu X; Li M; Zhang H; Hua S; Meng F; Yang H; Li X; Cao D
Phys Med Biol; 2020 Mar; 65(5):055012. PubMed ID: 31978901
[TBL] [Abstract][Full Text] [Related]
8. Transfer learning-based PET/CT three-dimensional convolutional neural network fusion of image and clinical information for prediction of EGFR mutation in lung adenocarcinoma.
Shao X; Ge X; Gao J; Niu R; Shi Y; Shao X; Jiang Z; Li R; Wang Y
BMC Med Imaging; 2024 Mar; 24(1):54. PubMed ID: 38438844
[TBL] [Abstract][Full Text] [Related]
9. Deep learning predicts epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.
Song J; Ding C; Huang Q; Luo T; Xu X; Chen Z; Li S
Med Phys; 2021 Dec; 48(12):7891-7899. PubMed ID: 34669994
[TBL] [Abstract][Full Text] [Related]
10. CT imaging-based histogram features for prediction of EGFR mutation status of bone metastases in patients with primary lung adenocarcinoma.
Shen TX; Liu L; Li WH; Fu P; Xu K; Jiang YQ; Pan F; Guo Y; Zhang MC
Cancer Imaging; 2019 Jun; 19(1):34. PubMed ID: 31174617
[TBL] [Abstract][Full Text] [Related]
11. Computed Tomography-derived intratumoral and peritumoral radiomics in predicting EGFR mutation in lung adenocarcinoma.
Shang Y; Chen W; Li G; Huang Y; Wang Y; Kui X; Li M; Zheng H; Zhao W; Liu J
Radiol Med; 2023 Dec; 128(12):1483-1496. PubMed ID: 37749461
[TBL] [Abstract][Full Text] [Related]
12. Identification of epidermal growth factor receptor mutations in pulmonary adenocarcinoma using dual-energy spectral computed tomography.
Li M; Zhang L; Tang W; Jin YJ; Qi LL; Wu N
Eur Radiol; 2019 Jun; 29(6):2989-2997. PubMed ID: 30367185
[TBL] [Abstract][Full Text] [Related]
13. Accurate prediction of epidermal growth factor receptor mutation status in early-stage lung adenocarcinoma, using radiomics and clinical features.
Zhu H; Song Y; Huang Z; Zhang L; Chen Y; Tao G; She Y; Sun X; Yu H
Asia Pac J Clin Oncol; 2022 Dec; 18(6):586-594. PubMed ID: 35098682
[TBL] [Abstract][Full Text] [Related]
14. Multiparametric MRI-Based Radiomics Approaches for Preoperative Prediction of EGFR Mutation Status in Spinal Bone Metastases in Patients with Lung Adenocarcinoma.
Jiang X; Ren M; Shuang X; Yang H; Shi D; Lai Q; Dong Y
J Magn Reson Imaging; 2021 Aug; 54(2):497-507. PubMed ID: 33638577
[TBL] [Abstract][Full Text] [Related]
15. Hybrid deep multi-task learning radiomics approach for predicting EGFR mutation status of non-small cell lung cancer in CT images.
Gong J; Fu F; Ma X; Wang T; Ma X; You C; Zhang Y; Peng W; Chen H; Gu Y
Phys Med Biol; 2023 Dec; 68(24):. PubMed ID: 37972417
[No Abstract] [Full Text] [Related]
16. Identifying EGFR mutations in lung adenocarcinoma by noninvasive imaging using radiomics features and random forest modeling.
Jia TY; Xiong JF; Li XY; Yu W; Xu ZY; Cai XW; Ma JC; Ren YC; Larsson R; Zhang J; Zhao J; Fu XL
Eur Radiol; 2019 Sep; 29(9):4742-4750. PubMed ID: 30778717
[TBL] [Abstract][Full Text] [Related]
17. Relationship between epidermal growth factor receptor mutations and CT features in patients with lung adenocarcinoma.
Zhang G; Zhao Z; Cao Y; Zhang J; Li S; Deng L; Zhou J
Clin Radiol; 2021 Jun; 76(6):473.e17-473.e24. PubMed ID: 33731263
[TBL] [Abstract][Full Text] [Related]
18. A multi-task deep learning model for EGFR genotyping prediction and GTV segmentation of brain metastasis.
Zhou Z; Wang M; Zhao R; Shao Y; Xing L; Qiu Q; Yin Y
J Transl Med; 2023 Nov; 21(1):788. PubMed ID: 37936137
[TBL] [Abstract][Full Text] [Related]
19. Prediction of EGFR mutations by conventional CT-features in advanced pulmonary adenocarcinoma.
Chen Y; Yang Y; Ma L; Zhu H; Feng T; Jiang S; Wei Y; Wang T; Sun X
Eur J Radiol; 2019 Mar; 112():44-51. PubMed ID: 30777218
[TBL] [Abstract][Full Text] [Related]
20. Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma.
Han X; Fan J; Li Y; Cao Y; Gu J; Jia X; Wang Y; Shi H
Sci Rep; 2021 Mar; 11(1):5679. PubMed ID: 33707479
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
