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A comparison of popular fertility awareness methods to a DBN model of the woman's monthly cycle

UNSPECIFIED (2012) A comparison of popular fertility awareness methods to a DBN model of the woman's monthly cycle. In: UNSPECIFIED.

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Abstract

Fertility Awareness Methods are effective, safe, and low-cost techniques for identifying the fertile days of a menstrual cycle. In this paper, we compare the effectiveness of predicting the fertile days by a Dynamic Bayesian Network model of the monthly cycle to 11 existing Fertility Awareness Methods. We base our comparison on a real data set of 7,017 cycles collected by 881 women. We demonstrate that the DBN model is more accurate than the best modern Fertility Awareness Methods, based on the observation of mucus, marking reasonably high percentage of days of the cycle as infertile. We argue that the DBN approach offers other advantages, such as predicting the ovulation day and being able to adjust its predictions to each woman's individual cycle.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Date: 1 December 2012
Date Type: Publication
Journal or Publication Title: Proceedings of the 6th European Workshop on Probabilistic Graphical Models, PGM 2012
Page Range: 219 - 226
Event Type: Conference
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9788415536574
Related URLs:
Date Deposited: 25 Jun 2013 15:56
Last Modified: 05 Jan 2019 15:59
URI: http://d-scholarship.pitt.edu/id/eprint/19110

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