BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

125 related articles for article (PubMed ID: 36460488)

  • 21. 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]  

  • 22. 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]  

  • 23. Development and Validation a Nomogram Incorporating CT Radiomics Signatures and Radiological Features for Differentiating Invasive Adenocarcinoma From Adenocarcinoma
    Shi L; Shi W; Peng X; Zhan Y; Zhou L; Wang Y; Feng M; Zhao J; Shan F; Liu L
    Front Oncol; 2021; 11():618677. PubMed ID: 33968722
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Development of a novel nomogram-based model incorporating 3D radiomic signatures and lung CT radiological features for differentiating invasive adenocarcinoma from adenocarcinoma in situ and minimally invasive adenocarcinoma.
    Ren H; Xiao Z; Ling C; Wang J; Wu S; Zeng Y; Li P
    Quant Imaging Med Surg; 2023 Jan; 13(1):237-248. PubMed ID: 36620176
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Developing a multi-institutional nomogram for assessing lung cancer risk in patients with 5-30 mm pulmonary nodules: a retrospective analysis.
    Jiang Y; Deng T; Huang Y; Ren B; He L; Pang M; Jiang L
    PeerJ; 2023; 11():e16539. PubMed ID: 38107565
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Application Potential of Radiomics based on the Unenhanced CT Image for the Identification of Benign or Malignant Pulmonary Nodules.
    Zhang L; Zeng B; Liu J; Lin H; Lei P; Xu R; Fan B
    Curr Med Imaging; 2023 Oct; ():. PubMed ID: 37916631
    [TBL] [Abstract][Full Text] [Related]  

  • 27. A Comprehensive Nomogram Combining CT Imaging with Clinical Features for Prediction of Lymph Node Metastasis in Stage I-IIIB Non-small Cell Lung Cancer.
    Zheng X; Shao J; Zhou L; Wang L; Ge Y; Wang G; Feng F
    Ther Innov Regul Sci; 2022 Jan; 56(1):155-167. PubMed ID: 34699046
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Can CT Radiomics Detect Acquired T790M Mutation and Predict Prognosis in Advanced Lung Adenocarcinoma With Progression After First- or Second-Generation EGFR TKIs?
    Yang X; Fang C; Li C; Gong M; Yi X; Lin H; Li K; Yu X
    Front Oncol; 2022; 12():904983. PubMed ID: 35875167
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Can Peritumoral Radiomics Improve the Prediction of Malignancy of Solid Pulmonary Nodule Smaller Than 2 cm?
    Wu S; Zhang N; Wu Z; Ren J; E L
    Acad Radiol; 2022 Feb; 29 Suppl 2():S47-S52. PubMed ID: 33189549
    [TBL] [Abstract][Full Text] [Related]  

  • 30. [Prediction of platinum-based chemotherapy sensitivity for epithelial ovarian cancer by multi-sequence MRI-based radiomic nomogram].
    Mao MM; Li HM; Shi J; Qiu QS; Feng F
    Zhonghua Yi Xue Za Zhi; 2022 Jan; 102(3):201-208. PubMed ID: 35042289
    [No Abstract]   [Full Text] [Related]  

  • 31. 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]  

  • 32. Preoperative MRI-Based Radiomic Machine-Learning Nomogram May Accurately Distinguish Between Benign and Malignant Soft-Tissue Lesions: A Two-Center Study.
    Wang H; Zhang J; Bao S; Liu J; Hou F; Huang Y; Chen H; Duan S; Hao D; Liu J
    J Magn Reson Imaging; 2020 Sep; 52(3):873-882. PubMed ID: 32112598
    [TBL] [Abstract][Full Text] [Related]  

  • 33. 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]  

  • 34. MRI-based radiomics nomogram for predicting temporal lobe injury after radiotherapy in nasopharyngeal carcinoma.
    Hou J; Li H; Zeng B; Pang P; Ai Z; Li F; Lu Q; Yu X
    Eur Radiol; 2022 Feb; 32(2):1106-1114. PubMed ID: 34467454
    [TBL] [Abstract][Full Text] [Related]  

  • 35. A CT-Based Radiomics Nomogram to Predict Complete Ablation of Pulmonary Malignancy: A Multicenter Study.
    Zhang G; Yang H; Zhu X; Luo J; Zheng J; Xu Y; Zheng Y; Wei Y; Mei Z; Shao G
    Front Oncol; 2022; 12():841678. PubMed ID: 35223526
    [TBL] [Abstract][Full Text] [Related]  

  • 36. 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]  

  • 37. A Machine Learning Model Based on PET/CT Radiomics and Clinical Characteristics Predicts ALK Rearrangement Status in Lung Adenocarcinoma.
    Chang C; Sun X; Wang G; Yu H; Zhao W; Ge Y; Duan S; Qian X; Wang R; Lei B; Wang L; Liu L; Ruan M; Yan H; Liu C; Chen J; Xie W
    Front Oncol; 2021; 11():603882. PubMed ID: 33738250
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Development and validation of a preoperative CT-based radiomic nomogram to predict pathology invasiveness in patients with a solitary pulmonary nodule: a machine learning approach, multicenter, diagnostic study.
    Huang L; Lin W; Xie D; Yu Y; Cao H; Liao G; Wu S; Yao L; Wang Z; Wang M; Wang S; Wang G; Zhang D; Yao S; He Z; Cho WC; Chen D; Zhang Z; Li W; Qiao G; Chan LW; Zhou H
    Eur Radiol; 2022 Mar; 32(3):1983-1996. PubMed ID: 34654966
    [TBL] [Abstract][Full Text] [Related]  

  • 39. An MRI-Based Radiomic Nomogram for Discrimination Between Malignant and Benign Sinonasal Tumors.
    Zhang H; Wang H; Hao D; Ge Y; Wan G; Zhang J; Liu S; Zhang Y; Xu D
    J Magn Reson Imaging; 2021 Jan; 53(1):141-151. PubMed ID: 32776393
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A clinical-radiomics nomogram for the preoperative prediction of lung metastasis in colorectal cancer patients with indeterminate pulmonary nodules.
    Hu T; Wang S; Huang L; Wang J; Shi D; Li Y; Tong T; Peng W
    Eur Radiol; 2019 Jan; 29(1):439-449. PubMed ID: 29948074
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.