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Evaluation of Models for the Recognition of Hadwritten Digits in Medical Forms

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5167))

Abstract

Medicine has benefited widely from the use of computational techniques, which are often employed in the analysis of data generated in medical clinics. Among the computational techniques used in these analyses are those from Knowledge Discovery in Databases (KDD). In order to apply KDD techniques in the analysis of clinical data, it is often necessary to map them into an adequate structured format. This paper presents an extension in a methodology to map medical forms into structured datasets, in which a sub-system for handwritten digit recognition is added to the overall mapping system.

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References

  1. Maletzke, A.G., Lee, H.D., Zalewski, W., Edson, R.F.V., Matsubara, T., Coy, C.S.R., Fagundes, J.J., Góes, J.R.N., Chung, W.F.: Mapeamento de informações médicas descritas em formulários para bases de dados estruturadas [in portuguese], Brasil, pp. 1–10 (2007)

    Google Scholar 

  2. Trier, O.D., Jain, A.K., Taxt, T.: Feature extraction methods for character recognition - a survey. Pattern Recognition 29, 641–662 (1996)

    Article  Google Scholar 

  3. Heutte, L., Paquet, T., Moreau, J.-V., Lecourtier, Y., Olivier, C.: A structural/statistical feature based vector for handwritten character recognition. Pattern Recognition Letters 19, 629–641 (1998)

    Article  Google Scholar 

  4. Arica, N., Yarman-Vural, F.: An overview of character recognition focused on off-line handwriting. IEEE Trans. Syst. Man and Cybern. Part C: Appl. and Rev. 31, 216–233 (2001)

    Google Scholar 

  5. Wang, X., Xie, K.: A novel direction chain code-based image retrieval. In: Proc. 4th Int. Conf. on Computer and Information Technology, pp. 190–193 (2004)

    Google Scholar 

  6. Lee, Y.: Handwritten digit recognition using k- nearest neighbor, radial-basis functions, and back-propagation neural networks. Neural Comp. 3(3), 440–449 (1991)

    Article  Google Scholar 

  7. Haykin, S.: Neural Networks - A Compreensive Foundation. Prentice-Hall, Englewood Cliffs (1999)

    Google Scholar 

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Ana L. C. Bazzan Mark Craven Natália F. Martins

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© 2008 Springer-Verlag Berlin Heidelberg

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Zalewski, W. et al. (2008). Evaluation of Models for the Recognition of Hadwritten Digits in Medical Forms. In: Bazzan, A.L.C., Craven, M., Martins, N.F. (eds) Advances in Bioinformatics and Computational Biology. BSB 2008. Lecture Notes in Computer Science(), vol 5167. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85557-6_19

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  • DOI: https://doi.org/10.1007/978-3-540-85557-6_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85556-9

  • Online ISBN: 978-3-540-85557-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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