These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
293 related articles for article (PubMed ID: 31376283)
41. Combining radiomic phenotypes of non-small cell lung cancer with liquid biopsy data may improve prediction of response to EGFR inhibitors. Yousefi B; LaRiviere MJ; Cohen EA; Buckingham TH; Yee SS; Black TA; Chien AL; Noël P; Hwang WT; Katz SI; Aggarwal C; Thompson JC; Carpenter EL; Kontos D Sci Rep; 2021 May; 11(1):9984. PubMed ID: 33976268 [TBL] [Abstract][Full Text] [Related]
42. Robust radiogenomics approach to the identification of EGFR mutations among patients with NSCLC from three different countries using topologically invariant Betti numbers. Ninomiya K; Arimura H; Chan WY; Tanaka K; Mizuno S; Muhammad Gowdh NF; Yaakup NA; Liam CK; Chai CS; Ng KH PLoS One; 2021; 16(1):e0244354. PubMed ID: 33428651 [TBL] [Abstract][Full Text] [Related]
43. [Application of radiomics captured from CT to predict the EGFR mutation status and TKIs therapeutic sensitivity of advanced lung adenocarcinoma]. Yang CS; Chen WD; Gong GZ; Li ZJ; Qiu QT; Yin Y Zhonghua Zhong Liu Za Zhi; 2019 Apr; 41(4):282-287. PubMed ID: 31014053 [No Abstract] [Full Text] [Related]
44. Systematic Review, Meta-Analysis and Radiomics Quality Score Assessment of CT Radiomics-Based Models Predicting Tumor EGFR Mutation Status in Patients with Non-Small-Cell Lung Cancer. Felfli M; Liu Y; Zerka F; Voyton C; Thinnes A; Jacques S; Iannessi A; Bodard S Int J Mol Sci; 2023 Jul; 24(14):. PubMed ID: 37511192 [TBL] [Abstract][Full Text] [Related]
45. Radiomics for Detection of the EGFR Mutation in Liver Metastatic NSCLC. Hou S; Fan Y; Wang X; Su J; Ren M; Wu Y; Zhou J; Qu M; Luo Y; Jiang W Acad Radiol; 2023 Jun; 30(6):1039-1046. PubMed ID: 35907759 [TBL] [Abstract][Full Text] [Related]
46. 18F-FDG uptake for prediction EGFR mutation status in non-small cell lung cancer. Guan J; Xiao NJ; Chen M; Zhou WL; Zhang YW; Wang S; Dai YM; Li L; Zhang Y; Li QY; Li XZ; Yang M; Wu HB; Chen LH; Liu LY Medicine (Baltimore); 2016 Jul; 95(30):e4421. PubMed ID: 27472739 [TBL] [Abstract][Full Text] [Related]
47. Efficient 18F-fluorodeoxyglucose positron emission tomography/computed tomography-based machine learning model for predicting epidermal growth factor receptor mutations in non-small cell lung cancer. Ruan D; Fang J; Teng X Q J Nucl Med Mol Imaging; 2024 Mar; 68(1):70-83. PubMed ID: 35420272 [TBL] [Abstract][Full Text] [Related]
48. Diffusion tensor and postcontrast T1-weighted imaging radiomics to differentiate the epidermal growth factor receptor mutation status of brain metastases from non-small cell lung cancer. Park YW; An C; Lee J; Han K; Choi D; Ahn SS; Kim H; Ahn SJ; Chang JH; Kim SH; Lee SK Neuroradiology; 2021 Mar; 63(3):343-352. PubMed ID: 32827069 [TBL] [Abstract][Full Text] [Related]
49. Impact of experimental design on PET radiomics in predicting somatic mutation status. Yip SSF; Parmar C; Kim J; Huynh E; Mak RH; Aerts HJWL Eur J Radiol; 2017 Dec; 97():8-15. PubMed ID: 29153372 [TBL] [Abstract][Full Text] [Related]
50. Development and validation of MRI-based radiomics signatures as new markers for preoperative assessment of EGFR mutation and subtypes from bone metastases. Fan Y; Dong Y; Sun X; Wang H; Zhao P; Wang H; Jiang X BMC Cancer; 2022 Aug; 22(1):889. PubMed ID: 35964032 [TBL] [Abstract][Full Text] [Related]
51. Comparison of therapeutic effects of EGFR-tyrosine kinase inhibitors on 19Del and L858R mutations in advanced lung adenocarcinoma and effect on cellular immune function. Zhou J; Ben S Thorac Cancer; 2018 Feb; 9(2):228-233. PubMed ID: 29222872 [TBL] [Abstract][Full Text] [Related]
52. Are exon 19 deletions and L858R different in early stage lung adenocarcinoma? Zhang Y; Ma Y; Li Y; Shen X; Yu Y; Pan Y; Zhang Y; Yu S; Zheng D; Zhao Y; Hu H; Sun Y; Zhang Y; Xiang J; Chen H J Cancer Res Clin Oncol; 2018 Jan; 144(1):165-171. PubMed ID: 29026990 [TBL] [Abstract][Full Text] [Related]
53. CT radiomics-based prediction of anaplastic lymphoma kinase and epidermal growth factor receptor mutations in lung adenocarcinoma. Choe J; Lee SM; Kim W; Do KH; Kim S; Choi S; Seo JB Eur J Radiol; 2021 Jun; 139():109710. PubMed ID: 33862316 [TBL] [Abstract][Full Text] [Related]
54. Using combined CT-clinical radiomics models to identify epidermal growth factor receptor mutation subtypes in lung adenocarcinoma. Huo JW; Luo TY; Diao L; Lv FJ; Chen WD; Yu RZ; Li Q Front Oncol; 2022; 12():846589. PubMed ID: 36059655 [TBL] [Abstract][Full Text] [Related]
55. CT texture analysis of lung adenocarcinoma: can Radiomic features be surrogate biomarkers for EGFR mutation statuses. Mei D; Luo Y; Wang Y; Gong J Cancer Imaging; 2018 Dec; 18(1):52. PubMed ID: 30547844 [TBL] [Abstract][Full Text] [Related]
56. A clinically practical radiomics-clinical combined model based on PET/CT data and nomogram predicts EGFR mutation in lung adenocarcinoma. Chang C; Zhou S; Yu H; Zhao W; Ge Y; Duan S; Wang R; Qian X; Lei B; Wang L; Liu L; Ruan M; Yan H; Sun X; Xie W Eur Radiol; 2021 Aug; 31(8):6259-6268. PubMed ID: 33544167 [TBL] [Abstract][Full Text] [Related]
57. Clinical efficacy of icotinib in lung cancer patients with different EGFR mutation status: a meta-analysis. Qu J; Wang YN; Xu P; Xiang DX; Yang R; Wei W; Qu Q Oncotarget; 2017 May; 8(20):33961-33971. PubMed ID: 28430623 [TBL] [Abstract][Full Text] [Related]
58. Development and Validation of Machine Learning Models to Predict Epidermal Growth Factor Receptor Mutation in Non-Small Cell Lung Cancer: A Multi-Center Retrospective Radiomics Study. Liu Y; Zhou J; Wu J; Wang W; Wang X; Guo J; Wang Q; Zhang X; Li D; Xie J; Ding X; Xing Y; Hu D Cancer Control; 2022; 29():10732748221092926. PubMed ID: 35417660 [TBL] [Abstract][Full Text] [Related]
59. Comprehensive Analysis of EGFR-Mutant Abundance and Its Effect on Efficacy of EGFR TKIs in Advanced NSCLC with EGFR Mutations. Li X; Cai W; Yang G; Su C; Ren S; Zhao C; Hu R; Chen X; Gao G; Guo Z; Li W; Zhou C; Hirsch FR J Thorac Oncol; 2017 Sep; 12(9):1388-1397. PubMed ID: 28624467 [TBL] [Abstract][Full Text] [Related]
60. Combination of computed tomography imaging-based radiomics and clinicopathological characteristics for predicting the clinical benefits of immune checkpoint inhibitors in lung cancer. Yang B; Zhou L; Zhong J; Lv T; Li A; Ma L; Zhong J; Yin S; Huang L; Zhou C; Li X; Ge YQ; Tao X; Zhang L; Son Y; Lu G Respir Res; 2021 Jun; 22(1):189. PubMed ID: 34183009 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]