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Bayesian methods for searching for optimal rules for timing intercourse to achieve pregnancy
Author(s) -
Scarpa Bruno,
Dunson David B.
Publication year - 2007
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.2846
Subject(s) - bayesian probability , computer science , pregnancy , artificial intelligence , biology , genetics
Abstract With societal trends towards increasing age at starting a pregnancy attempt, many women are concerned about achieving conception before the onset of infertility, which precedes menopause. Couples failing to conceive a pregnancy within 12 months are classified as clinically infertile, and may be recommended for assisted reproductive therapy (ART). Because many ART procedures are expensive and may convey an increased risk of adverse outcomes for the offspring, it is advantageous to decrease time to pregnancy by natural methods. One possibility is to intentionally time intercourse during the days of the menstrual cycle having the highest conception probabilities. This article proposes a Bayesian decision theoretic approach for searching for optimal rules for timing intercourse based on cycle day, secretions and other information. Good rules result in high conception probabilities while requiring minimal targeted intercourse. A biologically based statistical model is used to relate cycle day and biomarkers to the conception probability. A stochastic search procedure is then developed to search for rules with high expected utility, and the methods are applied to data from a recent Italian study. Copyright © 2007 John Wiley & Sons, Ltd.

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