Abstract
In clinical practice, making diagnostically crisp decisions is critical to successful treatment outcomes. However, there is no agreement on the operational methodology that is best suited to convert imprecise symptomatic information into crisp clinical treatment decision making. In this paper, a new computational decision making tool, Delphi-Neural Decision Making Processor (D-NDMP), is introduced as a preliminary study to apply to clinical practices for more successful and efficient operational decisions. A case study in a dental clinical decision involving a deep decay tooth is presented as an example to perform D-NDMP. The results yield a more reliable and confident opinion on the practical application of treatment decision in uncertain cases in a clinical decision making process.
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© 2014 Springer International Publishing Switzerland
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Song, KY., Gupta, M.M. (2014). Delphi-Neural Approach to Clinical Decision Making: A Preliminary Study. In: Jamshidi, M., Kreinovich, V., Kacprzyk, J. (eds) Advance Trends in Soft Computing. Studies in Fuzziness and Soft Computing, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-319-03674-8_39
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DOI: https://doi.org/10.1007/978-3-319-03674-8_39
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03673-1
Online ISBN: 978-3-319-03674-8
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