BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

177 related articles for article (PubMed ID: 36553681)

  • 1. Analysis of Breast Cancer Differences between China and Western Countries Based on Radiogenomics.
    Zhang Y; Yang L; Jiao X
    Genes (Basel); 2022 Dec; 13(12):. PubMed ID: 36553681
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Correlation of gene expression with magnetic resonance imaging features of retinoblastoma: a multi-center radiogenomics validation study.
    Jansen RW; Roohollahi K; Uner OE; de Jong Y; de Bloeme CM; Göricke S; Sirin S; Maeder P; Galluzzi P; Brisse HJ; Cardoen L; Castelijns JA; van der Valk P; Moll AC; Grossniklaus H; Hubbard GB; de Jong MC; Dorsman J; de Graaf P;
    Eur Radiol; 2024 Feb; 34(2):863-872. PubMed ID: 37615761
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine-learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time.
    Liao X; Cai B; Tian B; Luo Y; Song W; Li Y
    J Cell Mol Med; 2019 Jun; 23(6):4375-4385. PubMed ID: 31001929
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Radiogenomics analysis reveals the associations of dynamic contrast-enhanced-MRI features with gene expression characteristics, PAM50 subtypes, and prognosis of breast cancer.
    Ming W; Zhu Y; Bai Y; Gu W; Li F; Hu Z; Xia T; Dai Z; Yu X; Li H; Gu Y; Yuan S; Zhang R; Li H; Zhu W; Ding J; Sun X; Liu Y; Liu H; Liu X
    Front Oncol; 2022; 12():943326. PubMed ID: 35965527
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Breast MRI radiogenomics: Current status and research implications.
    Grimm LJ
    J Magn Reson Imaging; 2016 Jun; 43(6):1269-78. PubMed ID: 26663695
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Radiogenomics of breast cancer using dynamic contrast enhanced MRI and gene expression profiling.
    Yeh AC; Li H; Zhu Y; Zhang J; Khramtsova G; Drukker K; Edwards A; McGregor S; Yoshimatsu T; Zheng Y; Niu Q; Abe H; Mueller J; Conzen S; Ji Y; Giger ML; Olopade OI
    Cancer Imaging; 2019 Jul; 19(1):48. PubMed ID: 31307537
    [TBL] [Abstract][Full Text] [Related]  

  • 7. [Selection of Radiomic Features for the Classification of Triple-negative Breast Cancer Based on Radiogenomics].
    Kai C; Ishimaru M; Uchiyama Y; Shiraishi J; Shinohara N; Fujita H
    Nihon Hoshasen Gijutsu Gakkai Zasshi; 2019; 75(1):24-31. PubMed ID: 30662029
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Imaging and the completion of the omics paradigm in breast cancer.
    Leithner D; Horvat JV; Ochoa-Albiztegui RE; Thakur S; Wengert G; Morris EA; Helbich TH; Pinker K
    Radiologe; 2018 Nov; 58(Suppl 1):7-13. PubMed ID: 29947931
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Identification of candidate biomarkers correlated with poor prognosis of breast cancer based on bioinformatics analysis.
    Chen G; Yu M; Cao J; Zhao H; Dai Y; Cong Y; Qiao G
    Bioengineered; 2021 Dec; 12(1):5149-5161. PubMed ID: 34384030
    [TBL] [Abstract][Full Text] [Related]  

  • 10. MRI radiogenomics for intelligent diagnosis of breast tumors and accurate prediction of neoadjuvant chemotherapy responses-a review.
    Yin XX; Hadjiloucas S; Zhang Y; Tian Z
    Comput Methods Programs Biomed; 2022 Feb; 214():106510. PubMed ID: 34852935
    [TBL] [Abstract][Full Text] [Related]  

  • 11. MRI-based radiogenomics analysis for predicting genetic alterations in oncogenic signalling pathways in invasive breast carcinoma.
    Lin P; Liu WK; Li X; Wan D; Qin H; Li Q; Chen G; He Y; Yang H
    Clin Radiol; 2020 Jul; 75(7):561.e1-561.e11. PubMed ID: 32183997
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Breast Cancer Radiogenomics: Current Status and Future Directions.
    Grimm LJ; Mazurowski MA
    Acad Radiol; 2020 Jan; 27(1):39-46. PubMed ID: 31818385
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A radiogenomics biomarker based on immunological heterogeneity for non-invasive prognosis of renal clear cell carcinoma.
    Gao J; Ye F; Han F; Jiang H; Zhang J
    Front Immunol; 2022; 13():956679. PubMed ID: 36177018
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Texture analysis using machine learning-based 3-T magnetic resonance imaging for predicting recurrence in breast cancer patients treated with neoadjuvant chemotherapy.
    Eun NL; Kang D; Son EJ; Youk JH; Kim JA; Gweon HM
    Eur Radiol; 2021 Sep; 31(9):6916-6928. PubMed ID: 33693994
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.
    Yu Y; He Z; Ouyang J; Tan Y; Chen Y; Gu Y; Mao L; Ren W; Wang J; Lin L; Wu Z; Liu J; Ou Q; Hu Q; Li A; Chen K; Li C; Lu N; Li X; Su F; Liu Q; Xie C; Yao H
    EBioMedicine; 2021 Jul; 69():103460. PubMed ID: 34233259
    [TBL] [Abstract][Full Text] [Related]  

  • 16. TCGA-TCIA Impact on Radiogenomics Cancer Research: A Systematic Review.
    Zanfardino M; Pane K; Mirabelli P; Salvatore M; Franzese M
    Int J Mol Sci; 2019 Nov; 20(23):. PubMed ID: 31795520
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Novel imaging techniques of rectal cancer: what do radiomics and radiogenomics have to offer? A literature review.
    Horvat N; Bates DDB; Petkovska I
    Abdom Radiol (NY); 2019 Nov; 44(11):3764-3774. PubMed ID: 31055615
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Machine Learning Approaches to Radiogenomics of Breast Cancer using Low-Dose Perfusion Computed Tomography: Predicting Prognostic Biomarkers and Molecular Subtypes.
    Park EK; Lee KS; Seo BK; Cho KR; Woo OH; Son GS; Lee HY; Chang YW
    Sci Rep; 2019 Nov; 9(1):17847. PubMed ID: 31780739
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Background, current role, and potential applications of radiogenomics.
    Pinker K; Shitano F; Sala E; Do RK; Young RJ; Wibmer AG; Hricak H; Sutton EJ; Morris EA
    J Magn Reson Imaging; 2018 Mar; 47(3):604-620. PubMed ID: 29095543
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 9.