BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

624 related articles for article (PubMed ID: 31533838)

  • 1. Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution.
    Ji Y; Li H; Edwards AV; Papaioannou J; Ma W; Liu P; Giger ML
    Cancer Imaging; 2019 Sep; 19(1):64. PubMed ID: 31533838
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Role of sureness in evaluating AI/CADx: Lesion-based repeatability of machine learning classification performance on breast MRI.
    Whitney HM; Drukker K; Vieceli M; Van Dusen A; de Oliveira M; Abe H; Giger ML
    Med Phys; 2024 Mar; 51(3):1812-1821. PubMed ID: 37602841
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Artificial Intelligence Applied to Breast MRI for Improved Diagnosis.
    Jiang Y; Edwards AV; Newstead GM
    Radiology; 2021 Jan; 298(1):38-46. PubMed ID: 33078996
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Characterization of spatiotemporal changes for the classification of dynamic contrast-enhanced magnetic-resonance breast lesions.
    Milenković J; Hertl K; Košir A; Zibert J; Tasič JF
    Artif Intell Med; 2013 Jun; 58(2):101-14. PubMed ID: 23548472
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Multimodality computer-aided breast cancer diagnosis with FFDM and DCE-MRI.
    Yuan Y; Giger ML; Li H; Bhooshan N; Sennett CA
    Acad Radiol; 2010 Sep; 17(9):1158-67. PubMed ID: 20692620
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A machine learning approach for differentiating malignant from benign enhancing foci on breast MRI.
    D'Amico NC; Grossi E; Valbusa G; Rigiroli F; Colombo B; Buscema M; Fazzini D; Ali M; Malasevschi A; Cornalba G; Papa S
    Eur Radiol Exp; 2020 Jan; 4(1):5. PubMed ID: 31993839
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Radiomics Analysis Based on Automatic Image Segmentation of DCE-MRI for Predicting Triple-Negative and Nontriple-Negative Breast Cancer.
    Ma M; Gan L; Jiang Y; Qin N; Li C; Zhang Y; Wang X
    Comput Math Methods Med; 2021; 2021():2140465. PubMed ID: 34422088
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Computer-aided diagnosis for dynamic contrast-enhanced breast MRI of mass-like lesions using a multiparametric model combining a selection of morphological, kinetic, and spatiotemporal features.
    Agliozzo S; De Luca M; Bracco C; Vignati A; Giannini V; Martincich L; Carbonaro LA; Bert A; Sardanelli F; Regge D
    Med Phys; 2012 Apr; 39(4):1704-15. PubMed ID: 22482596
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Textural analysis of early-phase spatiotemporal changes in contrast enhancement of breast lesions imaged with an ultrafast DCE-MRI protocol.
    Milenković J; Dalmış MU; Žgajnar J; Platel B
    Med Phys; 2017 Sep; 44(9):4652-4664. PubMed ID: 28622412
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Radiomic Machine Learning for Characterization of Prostate Lesions with MRI: Comparison to ADC Values.
    Bonekamp D; Kohl S; Wiesenfarth M; Schelb P; Radtke JP; Götz M; Kickingereder P; Yaqubi K; Hitthaler B; Gählert N; Kuder TA; Deister F; Freitag M; Hohenfellner M; Hadaschik BA; Schlemmer HP; Maier-Hein KH
    Radiology; 2018 Oct; 289(1):128-137. PubMed ID: 30063191
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI.
    Chen W; Giger ML; Bick U; Newstead GM
    Med Phys; 2006 Aug; 33(8):2878-87. PubMed ID: 16964864
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Prediction of malignancy by a radiomic signature from contrast agent-free diffusion MRI in suspicious breast lesions found on screening mammography.
    Bickelhaupt S; Paech D; Kickingereder P; Steudle F; Lederer W; Daniel H; Götz M; Gählert N; Tichy D; Wiesenfarth M; Laun FB; Maier-Hein KH; Schlemmer HP; Bonekamp D
    J Magn Reson Imaging; 2017 Aug; 46(2):604-616. PubMed ID: 28152264
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A computer-aided diagnosis system for breast DCE-MRI at high spatiotemporal resolution.
    Dalmış MU; Gubern-Mérida A; Vreemann S; Karssemeijer N; Mann R; Platel B
    Med Phys; 2016 Jan; 43(1):84. PubMed ID: 26745902
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Artificial Intelligence-Based Classification of Breast Lesions Imaged With a Multiparametric Breast MRI Protocol With Ultrafast DCE-MRI, T2, and DWI.
    Dalmiş MU; Gubern-Mérida A; Vreemann S; Bult P; Karssemeijer N; Mann R; Teuwen J
    Invest Radiol; 2019 Jun; 54(6):325-332. PubMed ID: 30652985
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A new quantitative image analysis method for improving breast cancer diagnosis using DCE-MRI examinations.
    Yang Q; Li L; Zhang J; Shao G; Zheng B
    Med Phys; 2015 Jan; 42(1):103-9. PubMed ID: 25563251
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Performance evaluation of texture analysis based on kinetic parametric maps from breast DCE-MRI in classifying benign from malignant lesions.
    Jiang Z; Yin J
    J Surg Oncol; 2020 Jun; 121(8):1181-1190. PubMed ID: 32167588
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Potential of computer-aided diagnosis of high spectral and spatial resolution (HiSS) MRI in the classification of breast lesions.
    Bhooshan N; Giger M; Medved M; Li H; Wood A; Yuan Y; Lan L; Marquez A; Karczmar G; Newstead G
    J Magn Reson Imaging; 2014 Jan; 39(1):59-67. PubMed ID: 24023011
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Multilevel analysis of spatiotemporal association features for differentiation of tumor enhancement patterns in breast DCE-MRI.
    Lee SH; Kim JH; Cho N; Park JS; Yang Z; Jung YS; Moon WK
    Med Phys; 2010 Aug; 37(8):3940-56. PubMed ID: 20879557
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 32.