BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

115 related articles for article (PubMed ID: 38591974)

  • 1. Predicting Invasiveness of Lung Adenocarcinoma at Chest CT with Deep Learning Ternary Classification Models.
    Pan Z; Hu G; Zhu Z; Tan W; Han W; Zhou Z; Song W; Yu Y; Song L; Jin Z
    Radiology; 2024 Apr; 311(1):e232057. PubMed ID: 38591974
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Lung-PNet: An Automated Deep Learning Model for the Diagnosis of Invasive Adenocarcinoma in Pure Ground-Glass Nodules on Chest CT.
    Qi K; Wang K; Wang X; Zhang YD; Lin G; Zhang X; Liu H; Huang W; Wu J; Zhao K; Liu J; Li J; Zhang X
    AJR Am J Roentgenol; 2024 Jan; 222(1):e2329674. PubMed ID: 37493322
    [No Abstract]   [Full Text] [Related]  

  • 3. A nomogram for predicting invasiveness of lung adenocarcinoma manifesting as pure ground-glass nodules: incorporating subjective CT signs and histogram parameters based on artificial intelligence.
    Gao R; Gao Y; Zhang J; Zhu C; Zhang Y; Yan C
    J Cancer Res Clin Oncol; 2023 Nov; 149(17):15323-15333. PubMed ID: 37624396
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Diagnosis of Invasive Lung Adenocarcinoma Based on Chest CT Radiomic Features of Part-Solid Pulmonary Nodules: A Multicenter Study.
    Wu G; Woodruff HC; Shen J; Refaee T; Sanduleanu S; Ibrahim A; Leijenaar RTH; Wang R; Xiong J; Bian J; Wu J; Lambin P
    Radiology; 2020 Nov; 297(2):451-458. PubMed ID: 32840472
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images.
    Gong J; Liu J; Hao W; Nie S; Zheng B; Wang S; Peng W
    Eur Radiol; 2020 Apr; 30(4):1847-1855. PubMed ID: 31811427
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Preoperative CT-based Deep Learning Model for Predicting Disease-Free Survival in Patients with Lung Adenocarcinomas.
    Kim H; Goo JM; Lee KH; Kim YT; Park CM
    Radiology; 2020 Jul; 296(1):216-224. PubMed ID: 32396042
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Fusion of CT images and clinical variables based on deep learning for predicting invasiveness risk of stage I lung adenocarcinoma.
    Huang H; Zheng D; Chen H; Wang Y; Chen C; Xu L; Li G; Wang Y; He X; Li W
    Med Phys; 2022 Oct; 49(10):6384-6394. PubMed ID: 35938604
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. CT Characteristics for Predicting Invasiveness in Pulmonary Pure Ground-Glass Nodules.
    Chu ZG; Li WJ; Fu BJ; Lv FJ
    AJR Am J Roentgenol; 2020 Aug; 215(2):351-358. PubMed ID: 32348187
    [No Abstract]   [Full Text] [Related]  

  • 12. A radiomics study to predict invasive pulmonary adenocarcinoma appearing as pure ground-glass nodules.
    Cai J; Liu H; Yuan H; Wu Y; Xu Q; Lv Y; Li J; Fu J; Ye J
    Clin Radiol; 2021 Feb; 76(2):143-151. PubMed ID: 33187676
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predicting benign, preinvasive, and invasive lung nodules on computed tomography scans using machine learning.
    Ashraf SF; Yin K; Meng CX; Wang Q; Wang Q; Pu J; Dhupar R
    J Thorac Cardiovasc Surg; 2022 Apr; 163(4):1496-1505.e10. PubMed ID: 33726909
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Hybrid Clinical-Radiomics Model for Precisely Predicting the Invasiveness of Lung Adenocarcinoma Manifesting as Pure Ground-Glass Nodule.
    Song L; Xing T; Zhu Z; Han W; Fan G; Li J; Du H; Song W; Jin Z; Zhang G
    Acad Radiol; 2021 Sep; 28(9):e267-e277. PubMed ID: 32534967
    [TBL] [Abstract][Full Text] [Related]  

  • 15. CT quantitative parameters to predict the invasiveness of lung pure ground-glass nodules (pGGNs).
    Han L; Zhang P; Wang Y; Gao Z; Wang H; Li X; Ye Z
    Clin Radiol; 2018 May; 73(5):504.e1-504.e7. PubMed ID: 29397913
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Measuring pure ground-glass nodules on computed tomography: assessing agreement between a commercially available deep learning algorithm and radiologists' readings.
    Zuo Z; Wang P; Zeng W; Qi W; Zhang W
    Acta Radiol; 2023 Apr; 64(4):1422-1430. PubMed ID: 36317301
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Determining the invasiveness of ground-glass nodules using a 3D multi-task network.
    Yu Y; Wang N; Huang N; Liu X; Zheng Y; Fu Y; Li X; Wu H; Xu J; Cheng J
    Eur Radiol; 2021 Sep; 31(9):7162-7171. PubMed ID: 33665717
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Discriminating invasive adenocarcinoma among lung pure ground-glass nodules: a multi-parameter prediction model.
    Hu F; Huang H; Jiang Y; Feng M; Wang H; Tang M; Zhou Y; Tan X; Liu Y; Xu C; Ding N; Bai C; Hu J; Yang D; Zhang Y
    J Thorac Dis; 2021 Sep; 13(9):5383-5394. PubMed ID: 34659805
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Deep learning-based differentiation of invasive adenocarcinomas from preinvasive or minimally invasive lesions among pulmonary subsolid nodules.
    Park S; Park G; Lee SM; Kim W; Park H; Jung K; Seo JB
    Eur Radiol; 2021 Aug; 31(8):6239-6247. PubMed ID: 33555355
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Computed Tomography Findings for Predicting Invasiveness of Lung Adenocarcinomas Manifesting as Pure Ground-Glass Nodules.
    Park J; Doo KW; Sung YE; Jung JI; Chang S
    Can Assoc Radiol J; 2023 Feb; 74(1):137-146. PubMed ID: 35840350
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 6.