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

Dariusz Radomski, Zbigniew Lewandowski, Piotr I. Roszkowski
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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This study applies generalized additive models to analyze reproductive risk factors associated with endometrioid cysts, addressing the inability of standard logistic regression to assess nonlinearity between study factors and disease occurrence. The authors discuss theoretical similarities and differences between generalized additive models and neural networks while proposing a new etiological aspect for these cysts based on their findings regarding menstrual cycle courses. The paper does not explicitly discuss adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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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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