Behavior patterns in hormonal treatments using fuzzy logic models
Assisted reproductive technologies are a combination of medical strategies designed to treat infertility patients. Ideal stimulation treatment has to be individualized, but one of the main challenges which clinicians face in the everyday clinic is how to select the best medical protocol for a patient. This work aims to look for behavior patterns in this kind of treatments, using fuzzy logic models with the objective of helping gynecologists and embryologists to make decisions that could improve the process of in vitro fertilization. For this purpose, a real-world dataset composed of one hundred and twenty-three (123) patients and five hundred and fifty-nine (559) treatments applied in relation to such patients provided by an assisted reproduction clinic, has been used to obtain the fuzzy models. As conclusion, this work corroborates some known clinic experiences, provides some new ones and proposes a set of questions to be solved in future experiments.
KeywordsHormonal treatments IVF Fuzzy logic Data mining
This research has been supported by the MeGUS project (TIN2013-46928-C3-3-R), Pololas project (TIN2016-76956-C3-2-R), by the SoftPLM Network (TIN2015-71938-REDT) of the Spanish the Ministry of Economy and Competitiveness and Fujitsu Laboratories of Europe (FLE).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interests.
This article does not contain any studies with human participants or animals performed by any of the authors.
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