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    Classification of Sperm Cells According to their Chromosomic Content Using a Neural Network Trained with a Genetic Algorithm

    Date
    2003
    Author
    Kuri, A
    Ortiz, M
    Zenteno, D
    Penaloza, R
    Metadata
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    Abstract
    A priori determination of the sex of a human individual before gestation is a desirable goal in some cases. To achieve this, it is necessary to perform the separation of sperm cells containing either X or Y chromosomes. As is well known, male sex depends on the presence of chromosome Y. Once this separation is achieved in principle, we require to determine, with a high degree of accuracy, whether the sperm cells of interest contain the desired X or Y chromosomes. If we are able to obtain certain simple measurements regarding the sperm cells under consideration we will be able to control the fertilization process reliably. In this paper we report a method which allows for non-invasive verification of the characteristics of the separated sperm. We determined a set of easily measurable characteristics. From a sample drawn from previously cropped sperm we trained a neural network with a genetic algorithm. The trained network was able to perform a posteriori classification with an error much smaller than 1%. This percentage of efficiency is better than the ones reported in centers of assisted fecundation.
    URI
    http://dx.doi.org/10.1109/IEMBS.2003.1280246
    http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1280246&tag=1
    http://hdl.handle.net/10863/1452
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