BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

169 related articles for article (PubMed ID: 35042290)

  • 1. [Establishment and analysis of prediction model for invasive subsolid pulmonary nodules based on radiomics].
    Wu XL; Xu QZ; Chen T; Wang FL; Jiang WH; Lyu GM; Lu G
    Zhonghua Yi Xue Za Zhi; 2022 Jan; 102(3):209-215. PubMed ID: 35042290
    [No Abstract]   [Full Text] [Related]  

  • 2. A computerized tomography-based radiomic model for assessing the invasiveness of lung adenocarcinoma manifesting as ground-glass opacity nodules.
    Zhu M; Yang Z; Wang M; Zhao W; Zhu Q; Shi W; Yu H; Liang Z; Chen L
    Respir Res; 2022 Apr; 23(1):96. PubMed ID: 35429974
    [TBL] [Abstract][Full Text] [Related]  

  • 3. [Value of CT Features on Differential Diagnosis of Pulmonary Subsolid Nodules and Degree of invasion Prediction in Pulmonary Adenocarcinoma].
    Guo F; Li X; Wang X; Zheng W; Wang Q; Song W; Yu T; Fan Y; Wang Y
    Zhongguo Fei Ai Za Zhi; 2018 Jun; 21(6):451-457. PubMed ID: 29945703
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Whole-Lesion Computed Tomography-Based Entropy Parameters for the Differentiation of Minimally Invasive and Invasive Adenocarcinomas Appearing as Pulmonary Subsolid Nodules.
    Chen X; Feng B; Chen Y; Hao Y; Duan X; Cui E; Liu Z; Zhang C; Long W
    J Comput Assist Tomogr; 2019; 43(5):817-824. PubMed ID: 31343995
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A comparative study to evaluate CT-based semantic and radiomic features in preoperative diagnosis of invasive pulmonary adenocarcinomas manifesting as subsolid nodules.
    Wu YJ; Liu YC; Liao CY; Tang EK; Wu FZ
    Sci Rep; 2021 Jan; 11(1):66. PubMed ID: 33462251
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Radiomic signature based on CT imaging to distinguish invasive adenocarcinoma from minimally invasive adenocarcinoma in pure ground-glass nodules with pleural contact.
    Jiang Y; Che S; Ma S; Liu X; Guo Y; Liu A; Li G; Li Z
    Cancer Imaging; 2021 Jan; 21(1):1. PubMed ID: 33407884
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Thin-slice computed tomography enables to classify pulmonary subsolid nodules into pre-invasive lesion/minimally invasive adenocarcinoma and invasive adenocarcinoma: a retrospective study.
    Li M; Zhu L; Lv Y; Shen L; Han Y; Ye B
    Sci Rep; 2023 Apr; 13(1):6999. PubMed ID: 37117233
    [TBL] [Abstract][Full Text] [Related]  

  • 8. CT features and quantitative analysis of subsolid nodule lung adenocarcinoma for pathological classification prediction.
    Li X; Zhang W; Yu Y; Zhang G; Zhou L; Wu Z; Liu B
    BMC Cancer; 2020 Jan; 20(1):60. PubMed ID: 31992239
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Effect of CT window settings on size measurements of the solid component in subsolid nodules: evaluation of prediction efficacy of the degree of pathological malignancy in lung adenocarcinoma.
    Li Q; Gu YF; Fan L; Li QC; Xiao Y; Liu SY
    Br J Radiol; 2018 Jul; 91(1088):20180251. PubMed ID: 29791206
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Radiomics for differentiating minimally invasive adenocarcinoma from precursor lesions in pure ground-glass opacities on chest computed tomography.
    Zhu YQ; Liu C; Mo Y; Dong H; Huang C; Duan YN; Tang LL; Chu YY; Qin J
    Br J Radiol; 2022 Jun; 95(1134):20210768. PubMed ID: 35262392
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Radiomics for lung adenocarcinoma manifesting as pure ground-glass nodules: invasive prediction.
    Sun Y; Li C; Jin L; Gao P; Zhao W; Ma W; Tan M; Wu W; Duan S; Shan Y; Li M
    Eur Radiol; 2020 Jul; 30(7):3650-3659. PubMed ID: 32162003
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A triple-classification for the evaluation of lung nodules manifesting as pure ground-glass sign: a CT-based radiomic analysis.
    Yu Z; Xu C; Zhang Y; Ji F
    BMC Med Imaging; 2022 Jul; 22(1):133. PubMed ID: 35896975
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Radiomic-Based Quantitative CT Analysis of Pure Ground-Glass Nodules to Predict the Invasiveness of Lung Adenocarcinoma.
    Xu F; Zhu W; Shen Y; Wang J; Xu R; Qutesh C; Song L; Gan Y; Pu C; Hu H
    Front Oncol; 2020; 10():872. PubMed ID: 32850301
    [No Abstract]   [Full Text] [Related]  

  • 14. Predicting the Ki-67 proliferation index in pulmonary adenocarcinoma patients presenting with subsolid nodules: construction of a nomogram based on CT images.
    Yan J; Xue X; Gao C; Guo Y; Wu L; Zhou C; Chen F; Xu M
    Quant Imaging Med Surg; 2022 Jan; 12(1):642-652. PubMed ID: 34993108
    [TBL] [Abstract][Full Text] [Related]  

  • 15. CT-Imaging Based Analysis of Invasive Lung Adenocarcinoma Presenting as Ground Glass Nodules Using Peri- and Intra-nodular Radiomic Features.
    Wu L; Gao C; Xiang P; Zheng S; Pang P; Xu M
    Front Oncol; 2020; 10():838. PubMed ID: 32537436
    [No Abstract]   [Full Text] [Related]  

  • 16. Feature-shared adaptive-boost deep learning for invasiveness classification of pulmonary subsolid nodules in CT images.
    Wang J; Chen X; Lu H; Zhang L; Pan J; Bao Y; Su J; Qian D
    Med Phys; 2020 Apr; 47(4):1738-1749. PubMed ID: 32020649
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Value of TSCT Features for Differentiating Preinvasive and Minimally Invasive Adenocarcinoma From Invasive Adenocarcinoma Presenting as Subsolid Nodules Smaller Than 3 cm.
    Wang H; Weng Q; Hui J; Fang S; Wu X; Mao W; Chen M; Zheng L; Wang Z; Zhao Z; Zhou L; Tu J; Xu M; Huang Y; Ji J
    Acad Radiol; 2020 Mar; 27(3):395-403. PubMed ID: 31201034
    [TBL] [Abstract][Full Text] [Related]  

  • 18. [Clinical Multi-features Analysis of Cystic Lung Adenocarcinoma 
and Construction of Invasive Risk Prediction Model].
    Wang Q; Fu C; Wang K; Ren Q; Chen A; Xu X; Chen L; Zhu Q
    Zhongguo Fei Ai Za Zhi; 2024 Apr; 27(4):266-275. PubMed ID: 38769829
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A simple prediction model using size measures for discrimination of invasive adenocarcinomas among incidental pulmonary subsolid nodules considered for resection.
    Kim H; Goo JM; Park CM
    Eur Radiol; 2019 Apr; 29(4):1674-1683. PubMed ID: 30255253
    [TBL] [Abstract][Full Text] [Related]  

  • 20. The predictive value of CT-based radiomics in differentiating indolent from invasive lung adenocarcinoma in patients with pulmonary nodules.
    She Y; Zhang L; Zhu H; Dai C; Xie D; Xie H; Zhang W; Zhao L; Zou L; Fei K; Sun X; Chen C
    Eur Radiol; 2018 Dec; 28(12):5121-5128. PubMed ID: 29869172
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.