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Visualization and Practical Use of Clinical Survey Medical Examination Results

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Book cover Advances in Self-Organizing Maps and Learning Vector Quantization

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 428))

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Abstract

At present , the Metabolic Syndrome (MS) is judged by checking whether a number of reference values are exceeded. It is regarded as non-metabolic if those values are not exceeded. Using our previously established non-ill area for these values, we evaluate their applicability in medical practice. We start with a clinical survey of medical checkup data and apply our methodology to six items of the checkup sheet: glucose metabolism, liver, diabetes, kidney, blood-general and inflamed-immunity. We outline our methodology, called Dr. Ningendock, and evaluate it on the results of the liver function.

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References

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Acknowledgments

The authors are very obliged to Prof. M. Van Hulle of KU Leuven, Belgium, for kindly reading and correcting our manuscript.

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Correspondence to Masaaki Ohkita or Eikou Gonda .

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© 2016 Springer International Publishing Switzerland

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Ohkita, M., Tokutaka, H., Kasezawa, N., Gonda, E. (2016). Visualization and Practical Use of Clinical Survey Medical Examination Results. In: Merényi, E., Mendenhall, M., O'Driscoll, P. (eds) Advances in Self-Organizing Maps and Learning Vector Quantization. Advances in Intelligent Systems and Computing, vol 428. Springer, Cham. https://doi.org/10.1007/978-3-319-28518-4_21

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  • DOI: https://doi.org/10.1007/978-3-319-28518-4_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28517-7

  • Online ISBN: 978-3-319-28518-4

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