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Journal Abstract Search

888 related items for PubMed ID: 17996432

  • 1. An automated cervical pre-cancerous diagnostic system.
    Mat-Isa NA, Mashor MY, Othman NH.
    Artif Intell Med; 2008 Jan; 42(1):1-11. PubMed ID: 17996432
    [Abstract] [Full Text] [Related]

  • 2. Proposed Sheffield quantitative criteria in cervical cytology to assist the diagnosis and grading of squamous intra-epithelial lesions, as some Bethesda system definitions require amendment.
    Slater DN, Rice S, Stewart R, Melling SE, Hewer EM, Smith JH.
    Cytopathology; 2005 Aug; 16(4):168-78. PubMed ID: 16048503
    [Abstract] [Full Text] [Related]

  • 3. [Classification of cytological smears of the cervix with neuronal methods].
    Kestler HA, Schulé M, Schwenker F, Neumann H, Mattfeldt T.
    Biomed Tech (Berl); 1999 Aug; 44(1-2):17-24. PubMed ID: 10194881
    [Abstract] [Full Text] [Related]

  • 4. Automatic detection of epileptiform events in EEG by a three-stage procedure based on artificial neural networks.
    Acir N, Oztura I, Kuntalp M, Baklan B, Güzeliş C.
    IEEE Trans Biomed Eng; 2005 Jan; 52(1):30-40. PubMed ID: 15651562
    [Abstract] [Full Text] [Related]

  • 5. Neural network classification of autoregressive features from electroencephalogram signals for brain-computer interface design.
    Huan NJ, Palaniappan R.
    J Neural Eng; 2004 Sep; 1(3):142-50. PubMed ID: 15876633
    [Abstract] [Full Text] [Related]

  • 6. Assessment of four neural network based classifiers to automatically detect red lesions in retinal images.
    García M, López MI, Alvarez D, Hornero R.
    Med Eng Phys; 2010 Dec; 32(10):1085-93. PubMed ID: 20739211
    [Abstract] [Full Text] [Related]

  • 7. Quantitative assessment of tumour extraction from dermoscopy images and evaluation of computer-based extraction methods for an automatic melanoma diagnostic system.
    Iyatomi H, Oka H, Saito M, Miyake A, Kimoto M, Yamagami J, Kobayashi S, Tanikawa A, Hagiwara M, Ogawa K, Argenziano G, Soyer HP, Tanaka M.
    Melanoma Res; 2006 Apr; 16(2):183-90. PubMed ID: 16567974
    [Abstract] [Full Text] [Related]

  • 8. Utility of multilayer perceptron neural network classifiers in the diagnosis of the obstructive sleep apnoea syndrome from nocturnal oximetry.
    Marcos JV, Hornero R, Alvarez D, Del Campo F, Zamarrón C, López M.
    Comput Methods Programs Biomed; 2008 Oct; 92(1):79-89. PubMed ID: 18672313
    [Abstract] [Full Text] [Related]

  • 9. Content-based medical image classification using a new hierarchical merging scheme.
    Pourghassem H, Ghassemian H.
    Comput Med Imaging Graph; 2008 Dec; 32(8):651-61. PubMed ID: 18789648
    [Abstract] [Full Text] [Related]

  • 10. Control chart pattern recognition using an optimized neural network and efficient features.
    Ebrahimzadeh A, Ranaee V.
    ISA Trans; 2010 Jul; 49(3):387-93. PubMed ID: 20403598
    [Abstract] [Full Text] [Related]

  • 11. An expert diagnostic system based on neural networks and image analysis techniques in the field of automated cytogenetics.
    Beksaç MS, Eskiizmirliler S, Cakar AN, Erkmen AM, Dağdeviren A, Lundsteen C.
    Technol Health Care; 1996 Mar; 3(4):217-29. PubMed ID: 8705397
    [Abstract] [Full Text] [Related]

  • 12. Trained artificial neural network for glaucoma diagnosis using visual field data: a comparison with conventional algorithms.
    Bizios D, Heijl A, Bengtsson B.
    J Glaucoma; 2007 Jan; 16(1):20-8. PubMed ID: 17224745
    [Abstract] [Full Text] [Related]

  • 13. [Data mining in diagnostic knowledge acquisition from patients with brain glioma].
    Yei C, Yang J, Geng D.
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2002 Sep; 19(3):426-30. PubMed ID: 12557514
    [Abstract] [Full Text] [Related]

  • 14. Morphological feature extraction for the classification of digital images of cancerous tissues.
    Thiran JP, Macq B.
    IEEE Trans Biomed Eng; 1996 Oct; 43(10):1011-20. PubMed ID: 9214818
    [Abstract] [Full Text] [Related]

  • 15. Neural network based detection of hard exudates in retinal images.
    García M, Sánchez CI, López MI, Abásolo D, Hornero R.
    Comput Methods Programs Biomed; 2009 Jan; 93(1):9-19. PubMed ID: 18778869
    [Abstract] [Full Text] [Related]

  • 16. Automatic recognition of five types of white blood cells in peripheral blood.
    Rezatofighi SH, Soltanian-Zadeh H.
    Comput Med Imaging Graph; 2011 Jun; 35(4):333-43. PubMed ID: 21300521
    [Abstract] [Full Text] [Related]

  • 17. Automated neonatal seizure detection: a multistage classification system through feature selection based on relevance and redundancy analysis.
    Aarabi A, Wallois F, Grebe R.
    Clin Neurophysiol; 2006 Feb; 117(2):328-40. PubMed ID: 16376606
    [Abstract] [Full Text] [Related]

  • 18. A combination of rough-based feature selection and RBF neural network for classification using gene expression data.
    Chiang JH, Ho SH.
    IEEE Trans Nanobioscience; 2008 Mar; 7(1):91-9. PubMed ID: 18334459
    [Abstract] [Full Text] [Related]

  • 19. Model comparison for automatic characterization and classification of average ERPs using visual oddball paradigm.
    Merzagora AC, Butti M, Polikar R, Izzetoglu M, Bunce S, Cerutti S, Bianchi AM, Onaral B.
    Clin Neurophysiol; 2009 Feb; 120(2):264-74. PubMed ID: 19062338
    [Abstract] [Full Text] [Related]

  • 20. Eigenvector methods for automated detection of electrocardiographic changes in partial epileptic patients.
    Ubeyli ED.
    IEEE Trans Inf Technol Biomed; 2009 Jul; 13(4):478-85. PubMed ID: 19273021
    [Abstract] [Full Text] [Related]

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