These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

213 related articles for article (PubMed ID: 36772592)

  • 1. A Two-Step Feature Selection Radiomic Approach to Predict Molecular Outcomes in Breast Cancer.
    Brancato V; Brancati N; Esposito G; La Rosa M; Cavaliere C; Allarà C; Romeo V; De Pietro G; Salvatore M; Aiello M; Sangiovanni M
    Sensors (Basel); 2023 Jan; 23(3):. PubMed ID: 36772592
    [TBL] [Abstract][Full Text] [Related]  

  • 2. DCE-MRI Pharmacokinetic-Based Phenotyping of Invasive Ductal Carcinoma: A Radiomic Study for Prediction of Histological Outcomes.
    Monti S; Aiello M; Incoronato M; Grimaldi AM; Moscarino M; Mirabelli P; Ferbo U; Cavaliere C; Salvatore M
    Contrast Media Mol Imaging; 2018; 2018():5076269. PubMed ID: 29581709
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine learning on MRI radiomic features: identification of molecular subtype alteration in breast cancer after neoadjuvant therapy.
    Liu HQ; Lin SY; Song YD; Mai SY; Yang YD; Chen K; Wu Z; Zhao HY
    Eur Radiol; 2023 Apr; 33(4):2965-2974. PubMed ID: 36418622
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Conditional generative adversarial network driven radiomic prediction of mutation status based on magnetic resonance imaging of breast cancer.
    Huang ZH; Chen L; Sun Y; Liu Q; Hu P
    J Transl Med; 2024 Mar; 22(1):226. PubMed ID: 38429796
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Prediction of the clinicopathological subtypes of breast cancer using a fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI.
    Ni M; Zhou X; Liu J; Yu H; Gao Y; Zhang X; Li Z
    BMC Cancer; 2020 Nov; 20(1):1073. PubMed ID: 33167903
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Radiomic Signatures Derived from Diffusion-Weighted Imaging for the Assessment of Breast Cancer Receptor Status and Molecular Subtypes.
    Leithner D; Bernard-Davila B; Martinez DF; Horvat JV; Jochelson MS; Marino MA; Avendano D; Ochoa-Albiztegui RE; Sutton EJ; Morris EA; Thakur SB; Pinker K
    Mol Imaging Biol; 2020 Apr; 22(2):453-461. PubMed ID: 31209778
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Generative adversarial network-based super-resolution of diffusion-weighted imaging: Application to tumour radiomics in breast cancer.
    Fan M; Liu Z; Xu M; Wang S; Zeng T; Gao X; Li L
    NMR Biomed; 2020 Aug; 33(8):e4345. PubMed ID: 32521567
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI.
    Braman NM; Etesami M; Prasanna P; Dubchuk C; Gilmore H; Tiwari P; Plecha D; Madabhushi A
    Breast Cancer Res; 2017 May; 19(1):57. PubMed ID: 28521821
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Joint Prediction of Breast Cancer Histological Grade and Ki-67 Expression Level Based on DCE-MRI and DWI Radiomics.
    Fan M; Yuan W; Zhao W; Xu M; Wang S; Gao X; Li L
    IEEE J Biomed Health Inform; 2020 Jun; 24(6):1632-1642. PubMed ID: 31794406
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Ultrasound-based radiomics model for predicting molecular biomarkers in breast cancer.
    Xu R; You T; Liu C; Lin Q; Guo Q; Zhong G; Liu L; Ouyang Q
    Front Oncol; 2023; 13():1216446. PubMed ID: 37583930
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Invasive ductal breast cancer: preoperative predict Ki-67 index based on radiomics of ADC maps.
    Zhang Y; Zhu Y; Zhang K; Liu Y; Cui J; Tao J; Wang Y; Wang S
    Radiol Med; 2020 Feb; 125(2):109-116. PubMed ID: 31696388
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Multiparametric MRI and Radiomics for the Prediction of HER2-Zero, -Low, and -Positive Breast Cancers.
    Ramtohul T; Djerroudi L; Lissavalid E; Nhy C; Redon L; Ikni L; Djelouah M; Journo G; Menet E; Cabel L; Malhaire C; Tardivon A
    Radiology; 2023 Aug; 308(2):e222646. PubMed ID: 37526540
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping as a quantitative imaging biomarker for prediction of immunohistochemical receptor status, proliferation rate, and molecular subtypes of breast cancer.
    Horvat JV; Bernard-Davila B; Helbich TH; Zhang M; Morris EA; Thakur SB; Ochoa-Albiztegui RE; Leithner D; Marino MA; Baltzer PA; Clauser P; Kapetas P; Bago-Horvath Z; Pinker K
    J Magn Reson Imaging; 2019 Sep; 50(3):836-846. PubMed ID: 30811717
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Apparent diffusion coefficient value measurements with diffusion magnetic resonance imaging correlated with the expression levels of estrogen and progesterone receptor in breast cancer: A meta-analysis.
    Meng L; Ma P
    J Cancer Res Ther; 2016; 12(1):36-42. PubMed ID: 27072207
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction and prognosis of biologically aggressive breast cancers by the combination of DWI/DCE-MRI and immunohistochemical tumor markers.
    Allarakha A; Gao Y; Jiang H; Wang PJ
    Discov Med; 2019 Jan; 27(146):7-15. PubMed ID: 30695671
    [TBL] [Abstract][Full Text] [Related]  

  • 16. DCE-MRI Radiomics Analysis in Differentiating Luminal A and Luminal B Breast Cancer Molecular Subtypes.
    Lafcı O; Celepli P; Seher Öztekin P; Koşar PN
    Acad Radiol; 2023 Jan; 30(1):22-29. PubMed ID: 35595629
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.
    Huang Y; Wei L; Hu Y; Shao N; Lin Y; He S; Shi H; Zhang X; Lin Y
    Front Oncol; 2021; 11():706733. PubMed ID: 34490107
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients.
    Tahmassebi A; Wengert GJ; Helbich TH; Bago-Horvath Z; Alaei S; Bartsch R; Dubsky P; Baltzer P; Clauser P; Kapetas P; Morris EA; Meyer-Baese A; Pinker K
    Invest Radiol; 2019 Feb; 54(2):110-117. PubMed ID: 30358693
    [TBL] [Abstract][Full Text] [Related]  

  • 19. MRI Radiomics of Breast Cancer: Machine Learning-Based Prediction of Lymphovascular Invasion Status.
    Kayadibi Y; Kocak B; Ucar N; Akan YN; Yildirim E; Bektas S
    Acad Radiol; 2022 Jan; 29 Suppl 1():S126-S134. PubMed ID: 34876340
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Radiomic features of Pk-DCE MRI parameters based on the extensive Tofts model in application of breast cancer.
    Zhou X; Gao F; Duan S; Zhang L; Liu Y; Zhou J; Bai G; Tao W
    Phys Eng Sci Med; 2020 Jun; 43(2):517-524. PubMed ID: 32524436
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.