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 *

103 related articles for article (PubMed ID: 15360765)

  • 1. Using a Bayesian network to predict the probability and type of breast cancer represented by microcalcifications on mammography.
    Burnside ES; Rubin DL; Shachter RD
    Stud Health Technol Inform; 2004; 107(Pt 1):13-7. PubMed ID: 15360765
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: initial experience.
    Burnside ES; Rubin DL; Fine JP; Shachter RD; Sisney GA; Leung WK
    Radiology; 2006 Sep; 240(3):666-73. PubMed ID: 16926323
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Malignant and benign clustered microcalcifications: automated feature analysis and classification.
    Jiang Y; Nishikawa RM; Wolverton DE; Metz CE; Giger ML; Schmidt RA; Vyborny CJ; Doi K
    Radiology; 1996 Mar; 198(3):671-8. PubMed ID: 8628853
    [TBL] [Abstract][Full Text] [Related]  

  • 4. On the interplay of machine learning and background knowledge in image interpretation by Bayesian networks.
    Velikova M; Lucas PJ; Samulski M; Karssemeijer N
    Artif Intell Med; 2013 Jan; 57(1):73-86. PubMed ID: 23395008
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The significance of mammographic calcifications in early breast cancer detection.
    Rosselli Del Turco M; Ciatto S; Bravetti P; Pacini P
    Radiol Med; 1986; 72(1-2):7-12. PubMed ID: 3008222
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Dynamic contrast-enhanced MR imaging in screening detected microcalcification lesions of the breast: is there any value?
    Uematsu T; Yuen S; Kasami M; Uchida Y
    Breast Cancer Res Treat; 2007 Jul; 103(3):269-81. PubMed ID: 17063274
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A Bayesian network for mammography.
    Burnside E; Rubin D; Shachter R
    Proc AMIA Symp; 2000; ():106-10. PubMed ID: 11079854
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A probabilistic expert system that provides automated mammographic-histologic correlation: initial experience.
    Burnside ES; Rubin DL; Shachter RD; Sohlich RE; Sickles EA
    AJR Am J Roentgenol; 2004 Feb; 182(2):481-8. PubMed ID: 14736686
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Detection of single and clustered microcalcifications in mammograms using fractals models and neural networks.
    Bocchi L; Coppini G; Nori J; Valli G
    Med Eng Phys; 2004 May; 26(4):303-12. PubMed ID: 15121055
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Use of microcalcification descriptors in BI-RADS 4th edition to stratify risk of malignancy.
    Burnside ES; Ochsner JE; Fowler KJ; Fine JP; Salkowski LR; Rubin DL; Sisney GA
    Radiology; 2007 Feb; 242(2):388-95. PubMed ID: 17255409
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Preliminary investigation of a Bayesian network for mammographic diagnosis of breast cancer.
    Kahn CE; Roberts LM; Wang K; Jenks D; Haddawy P
    Proc Annu Symp Comput Appl Med Care; 1995; ():208-12. PubMed ID: 8563269
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A quantitative analysis of the spatial relationships of grouped microcalcifications demonstrated on xeromammography in benign and malignant breast disease.
    Hansell DM; Cooke JC; Parsons CA; Evans SH; Dance DR; Bliss JM; Llesley I
    Br J Radiol; 1988 Jan; 61(721):21-5. PubMed ID: 2832028
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Using tissue texture surrounding calcification clusters to predict benign vs malignant outcomes.
    Thiele DL; Kimme-Smith C; Johnson TD; McCombs M; Bassett LW
    Med Phys; 1996 Apr; 23(4):549-55. PubMed ID: 9157269
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Contrast-enhanced MR imaging in patients with BI-RADS 3-5 microcalcifications.
    Cilotti A; Iacconi C; Marini C; Moretti M; Mazzotta D; Traino C; Naccarato AG; Piagneri V; Giaconi C; Bevilacqua G; Bartolozzi C
    Radiol Med; 2007 Mar; 112(2):272-86. PubMed ID: 17361370
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The predictive value of needle localization mammographically assisted biopsy of the breast.
    Senofsky GM; Davies RJ; Olson L; Skully P; Olshen R
    Surg Gynecol Obstet; 1990 Nov; 171(5):361-5. PubMed ID: 2237718
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Microcalcifications of non-palpable breast lesions detected by ultrasonography: correlation with mammography and histopathology.
    Huang CS; Wu CY; Chu JS; Lin JH; Hsu SM; Chang KJ
    Ultrasound Obstet Gynecol; 1999 Jun; 13(6):431-6. PubMed ID: 10423808
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predicting breast cancer invasion with artificial neural networks on the basis of mammographic features.
    Lo JY; Baker JA; Kornguth PJ; Iglehart JD; Floyd CE
    Radiology; 1997 Apr; 203(1):159-63. PubMed ID: 9122385
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Breast microcalcifications: multivariate analysis of radiologic and clinical factors for carcinoma.
    Fondrinier E; Lorimier G; Guerin-Boblet V; Bertrand AF; Mayras C; Dauver N
    World J Surg; 2002 Mar; 26(3):290-6. PubMed ID: 11865363
    [TBL] [Abstract][Full Text] [Related]  

  • 19. [Computer-aided segmentation, form analysis and classification of 2975 breast microcalcifications using 7-fold microfocus magnification mammography].
    Grunert JH; Khalifa R; Gmelin E
    Rofo; 2004 Dec; 176(12):1759-65. PubMed ID: 15573286
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Mammographic criteria for determining the diagnostic value of microcalcifications in the detection of early breast cancer.
    Yunus M; Ahmed N; Masroor I; Yaqoob J
    J Pak Med Assoc; 2004 Jan; 54(1):24-9. PubMed ID: 15058638
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.