An Application of a Generalized Additive Model for an Identification of a Nonlinear Relation between a Course of Menstrual Cycles and a Risk of Endometrioid Cysts

In: Advances in Soft Computing · 2008 · pp. 482–487 · doi:10.1007/978-3-540-68168-7_54 · W1510684546
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This paper applies generalized additive models to identify nonlinear relationships between menstrual cycle characteristics and endometrioid cyst risk, proposing a new etiological aspect for the condition.

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References

Agresti, A.: Categorical Data Analysis, 2nd edn. Wiley, Chichester (2002) Royston, P., Altman, D.G., Sauerbrei, W.: Dichotomizing continuous predictors in multiple regression: a bad idea. Stat. Med. 25(1), 127–141 (2006) Hornik, K., Stinchcombe, M., White, H.: Universal approximation of an unknown mapping and its derivatives using multilayer neural networks. Neural Networks 3, 551–560 (1990) Hastie, T.I., Tibshirani, R.I.: Generalized Additive models. CRC Press, Boca Raton (1990) Candiani, G.B., Danesino, V., Gastaldi, A., Parazzini, F., Ferraroni, M.: Reproductive and menstrual factors and risk of peritoneal and ovarian endometriosis. Fertil. Steril. 56, 230–234 (1991) Nisolle, M., Donnez, J.: Peritoneal endometriosis, ovarian endometriosis, and adenomyotic nodules of the rectovaginal septum are three different entities. Fertil. Steril. 68, 585–596 (1997) Anders, U., Korn, O.: Model selection in neural networks. Neural Networks 12, 309–323 (1999) Dehejia, R.: Practical propensity score matching. J Econometr. 125(1-2), 355–364 (2005) Hegland, M., McIntosh, I., Turlach, B.A.: A parallel solver for generalised additive models. Comp. Stat. Data. Anal. 31, 377–396 (1999) Author information Authors and Affiliations Editor information Rights and permissions Copyright information © 2008 Springer-Verlag Berlin Heidelberg About this paper Cite this paper Radomski, D., Lewandowski, Z., Roszkowski, P.I. (2008). An Application of a Generalized Additive Model for an Identification of a Nonlinear Relation between a Course of Menstrual Cycles and a Risk of Endometrioid Cysts. In: Pietka, E., Kawa, J. (eds) Information Technologies in Biomedicine. Advances in Soft Computing, vol 47. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68168-7_54 Download citation DOI: https://doi.org/10.1007/978-3-540-68168-7_54 Publisher Name: Springer, Berlin, Heidelberg Print ISBN: 978-3-540-68167-0 Online ISBN: 978-3-540-68168-7 eBook Packages: EngineeringEngineering (R0)Springer Nature Proceedings excluding Computer Science

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