BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

85 related articles for article (PubMed ID: 8978873)

  • 1. Potential of the back propagation neural network in the morphologic examination of thyroid lesions.
    Karakitsos P; Cochand-Priollet B; Guillausseau PJ; Pouliakis A
    Anal Quant Cytol Histol; 1996 Dec; 18(6):494-500. PubMed ID: 8978873
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Learning vector quantizer in the investigation of thyroid lesions.
    Karakitsos P; Cochand-Priollet B; Pouliakis A; Guillausseau PJ; Ioakim-Liossi A
    Anal Quant Cytol Histol; 1999 Jun; 21(3):201-8. PubMed ID: 10560492
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Cascaded learning vector quantizer neural networks for the discrimination of thyroid lesions.
    Varlatzidou A; Pouliakis A; Stamataki M; Meristoudis C; Margari N; Peros G; Panayiotides JG; Karakitsos P
    Anal Quant Cytol Histol; 2011 Dec; 33(6):323-34. PubMed ID: 22590810
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Application of the learning vector quantizer to the classification of breast lesions.
    Markopoulos C; Karakitsos P; Botsoli-Stergiou E; Pouliakis A; Ioakim-Liossi A; Kyrkou K; Gogas J
    Anal Quant Cytol Histol; 1997 Oct; 19(5):453-60. PubMed ID: 9349906
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Potential of radial basis function neural networks in discriminating benign from malignant lesions of the lower urinary tract.
    Karakitsos P; Pouliakis A; Kordalis G; Georgoulakis J; Kittas C; Kyroudes A
    Anal Quant Cytol Histol; 2005 Feb; 27(1):35-42. PubMed ID: 15794450
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Potential of the back propagation neural network in the discrimination of benign from malignant gastric cells.
    Karakitsos P; Stergiou EB; Pouliakis A; Tzivras M; Archimandritis A; Liossi AI; Kyrkou K
    Anal Quant Cytol Histol; 1996 Jun; 18(3):245-50. PubMed ID: 8790840
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Image cytometry of fine needle aspiration of thyroid epithelial lesions.
    Mahfouz SM; El-Sharkawy SL; Sharaf WM; El-din Hussein H; El-Nemr RS
    Appl Immunohistochem Mol Morphol; 2012 Jan; 20(1):25-30. PubMed ID: 21691199
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Computerized morphometric study on fine needle aspirates of cellular follicular lesions of the thyroid.
    Tseleni-Balafouta S; Kavantzas N; Paraskevakou H; Davaris P
    Anal Quant Cytol Histol; 2000 Aug; 22(4):323-6. PubMed ID: 10965408
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Detection of underlying characteristics of nuclear chromatin patterns of thyroid tumor cells using texture and factor analyses.
    Murata S; Mochizuki K; Nakazawa T; Kondo T; Nakamura N; Yamashita H; Urata Y; Ashihara T; Katoh R
    Cytometry; 2002 Nov; 49(3):91-5. PubMed ID: 12442308
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Does Hurthle cell lesion/neoplasm predict malignancy more than follicular lesion/neoplasm on thyroid fine-needle aspiration?
    Pu RT; Yang J; Wasserman PG; Bhuiya T; Griffith KA; Michael CW
    Diagn Cytopathol; 2006 May; 34(5):330-4. PubMed ID: 16604553
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Contribution of morphometry in the differential diagnosis of fine-needle thyroid aspirates.
    Karslioğlu Y; Celasun B; Günhan O
    Cytometry B Clin Cytom; 2005 May; 65(1):22-8. PubMed ID: 15779051
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Back propagation neural network in the discrimination of benign from malignant lower urinary tract lesions.
    Pantazopoulos D; Karakitsos P; Iokim-Liossi A; Pouliakis A; Botsoli-Stergiou E; Dimopoulos C
    J Urol; 1998 May; 159(5):1619-23. PubMed ID: 9554366
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Fine needle aspiration of the thyroid: can an image processing system improve differentiation?
    Harms H; Hofmann M; Ruschenburg I
    Anal Quant Cytol Histol; 2002 Jun; 24(3):147-53. PubMed ID: 12102126
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Application of artificial neural network for classification of thyroid follicular tumors.
    Shapiro NA; Poloz TL; Shkurupij VA; Tarkov MS; Poloz VV; Demin AV
    Anal Quant Cytol Histol; 2007 Apr; 29(2):87-94. PubMed ID: 17484272
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Discriminating benign from malignant thyroid lesions using artificial intelligence and statistical selection of morphometric features.
    Cochand-Priollet B; Koutroumbas K; Megalopoulou TM; Pouliakis A; Sivolapenko G; Karakitsos P
    Oncol Rep; 2006; 15 Spec no.():1023-6. PubMed ID: 16525694
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Static cytometry and neural networks in the discrimination of lower urinary system lesions.
    Pantazopoulos D; Karakitsos P; Pouliakis A; Iokim-Liossi A; Dimopoulos MA
    Urology; 1998 Jun; 51(6):946-50. PubMed ID: 9609631
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Neural network application in the discrimination of benign from malignant gastric cells.
    Karakitsos P; Pouliakis A; Koutroumbas K; Stergiou EB; Tzivras M; Archimandritis A; Liossi AI
    Anal Quant Cytol Histol; 2000 Feb; 22(1):63-9. PubMed ID: 10696462
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparative study of artificial neural networks in the discrimination between benign from malignant gastric cells.
    Karakitsos P; Stergiou EB; Pouliakis A; Tzivras M; Archimandritis A; Liossi A; Kyrkou K
    Anal Quant Cytol Histol; 1997 Apr; 19(2):145-52. PubMed ID: 9113307
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Computer-assisted cell morphometry and ploidy analysis in the assessment of thyroid follicular neoplasms.
    Frasoldati A; Flora M; Pesenti M; Caroggio A; Valcavil R
    Thyroid; 2001 Oct; 11(10):941-6. PubMed ID: 11716041
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Fine-needle aspiration of the macrofollicular and microfollicular subtypes of the follicular variant of papillary carcinoma of the thyroid.
    Mesonero CE; Jugle JE; Wilbur DC; Nayar R
    Cancer; 1998 Aug; 84(4):235-44. PubMed ID: 9723599
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 5.