BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

605 related articles for article (PubMed ID: 33148663)

  • 1. Radiomic Detection of EGFR Mutations in NSCLC.
    Rossi G; Barabino E; Fedeli A; Ficarra G; Coco S; Russo A; Adamo V; Buemi F; Zullo L; Dono M; De Luca G; Longo L; Dal Bello MG; Tagliamento M; Alama A; Cittadini G; Pronzato P; Genova C
    Cancer Res; 2021 Feb; 81(3):724-731. PubMed ID: 33148663
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Next-Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Algorithms.
    Shiri I; Maleki H; Hajianfar G; Abdollahi H; Ashrafinia S; Hatt M; Zaidi H; Oveisi M; Rahmim A
    Mol Imaging Biol; 2020 Aug; 22(4):1132-1148. PubMed ID: 32185618
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer.
    Le NQK; Kha QH; Nguyen VH; Chen YC; Cheng SJ; Chen CY
    Int J Mol Sci; 2021 Aug; 22(17):. PubMed ID: 34502160
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Usefulness of gradient tree boosting for predicting histological subtype and EGFR mutation status of non-small cell lung cancer on
    Koyasu S; Nishio M; Isoda H; Nakamoto Y; Togashi K
    Ann Nucl Med; 2020 Jan; 34(1):49-57. PubMed ID: 31659591
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Value of pre-therapy
    Zhang J; Zhao X; Zhao Y; Zhang J; Zhang Z; Wang J; Wang Y; Dai M; Han J
    Eur J Nucl Med Mol Imaging; 2020 May; 47(5):1137-1146. PubMed ID: 31728587
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer.
    Nair JKR; Saeed UA; McDougall CC; Sabri A; Kovacina B; Raidu BVS; Khokhar RA; Probst S; Hirsh V; Chankowsky J; Van Kempen LC; Taylor J
    Can Assoc Radiol J; 2021 Feb; 72(1):109-119. PubMed ID: 32063026
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Using contrast-enhanced CT and non-contrast-enhanced CT to predict EGFR mutation status in NSCLC patients-a radiomics nomogram analysis.
    Yang X; Liu M; Ren Y; Chen H; Yu P; Wang S; Zhang R; Dai H; Wang C
    Eur Radiol; 2022 Apr; 32(4):2693-2703. PubMed ID: 34807270
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Can CT radiomic analysis in NSCLC predict histology and EGFR mutation status?
    Digumarthy SR; Padole AM; Gullo RL; Sequist LV; Kalra MK
    Medicine (Baltimore); 2019 Jan; 98(1):e13963. PubMed ID: 30608433
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Radiomics signature: A potential and incremental predictor for EGFR mutation status in NSCLC patients, comparison with CT morphology.
    Tu W; Sun G; Fan L; Wang Y; Xia Y; Guan Y; Li Q; Zhang D; Liu S; Li Z
    Lung Cancer; 2019 Jun; 132():28-35. PubMed ID: 31097090
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Radiomics for the prediction of EGFR mutation subtypes in non-small cell lung cancer.
    Li S; Ding C; Zhang H; Song J; Wu L
    Med Phys; 2019 Oct; 46(10):4545-4552. PubMed ID: 31376283
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Deep learning-radiomics integrated noninvasive detection of epidermal growth factor receptor mutations in non-small cell lung cancer patients.
    Kim S; Lim JH; Kim CH; Roh J; You S; Choi JS; Lim JH; Kim L; Chang JW; Park D; Lee MW; Kim S; Heo J
    Sci Rep; 2024 Jan; 14(1):922. PubMed ID: 38195717
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Machine learning-based radiomics strategy for prediction of acquired EGFR T790M mutation following treatment with EGFR-TKI in NSCLC.
    Lu J; Ji X; Liu X; Jiang Y; Li G; Fang P; Li W; Zuo A; Guo Z; Yang S; Ji Y; Lu D
    Sci Rep; 2024 Jan; 14(1):446. PubMed ID: 38172228
    [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. Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.
    Gu Q; Feng Z; Liang Q; Li M; Deng J; Ma M; Wang W; Liu J; Liu P; Rong P
    Eur J Radiol; 2019 Sep; 118():32-37. PubMed ID: 31439255
    [TBL] [Abstract][Full Text] [Related]  

  • 17. CT-based nomogram for early identification of T790M resistance in metastatic non-small cell lung cancer before first-line epidermal growth factor receptor-tyrosine kinase inhibitors therapy.
    Li Y; Lv X; Wang Y; Xu Z; Lv Y; Hou D
    Eur Radiol Exp; 2023 Nov; 7(1):64. PubMed ID: 37914925
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Development and Validation of a Machine Learning Model to Explore Tyrosine Kinase Inhibitor Response in Patients With Stage IV EGFR Variant-Positive Non-Small Cell Lung Cancer.
    Song J; Wang L; Ng NN; Zhao M; Shi J; Wu N; Li W; Liu Z; Yeom KW; Tian J
    JAMA Netw Open; 2020 Dec; 3(12):e2030442. PubMed ID: 33331920
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Impact of feature harmonization on radiogenomics analysis: Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images.
    Shiri I; Amini M; Nazari M; Hajianfar G; Haddadi Avval A; Abdollahi H; Oveisi M; Arabi H; Rahmim A; Zaidi H
    Comput Biol Med; 2022 Mar; 142():105230. PubMed ID: 35051856
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 31.