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IUI mining: human expert guidance of information theoretic network approach

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Abstract

The intra uterine insemination (IUI) is an assisted reproductive technique, enabling infertile couples to achieve pregnancy. We propose the variation of information theoretic network approach which uses human expert guidance to knowledge mining and suggest some possible modifications to IUI treatment plan in order to improve overall success rates. The information theoretic network algorithm employs the statistic significance to construct the network. We propose a new algorithm by adding up the medical significant criteria from human expert to construct the information theoretic network. We found that this new algorithm give us more reasonable result to human expert than the original information theoretic approach. The reliability of the knowledge got from this new algorithm is more acceptable than the original algorithm. And also human experts accept and satisfy the knowledge got from this new algorithm than the original algorithm. This shows that using human expert guidance with the original information theoretic approach to be the new algorithm can give us better result.

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Authors and Affiliations

  1. School of Information Technologies, The University of Sydney, NSW, 2006, Australia

    S. Kooptiwoot & M. A. Salam

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  1. S. Kooptiwoot
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  2. M. A. Salam
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Correspondence to S. Kooptiwoot.

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Kooptiwoot, S., Salam, M. IUI mining: human expert guidance of information theoretic network approach. Soft Comput 10, 369–373 (2006). https://doi.org/10.1007/s00500-005-0496-6

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