started methodology
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@@ -41,11 +41,24 @@ throughout the menstrual cycle.
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\begin{figure}
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\centering
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\includegraphics[width=0.7\textwidth]{background_menstrual_cycle_physiology}
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\includegraphics[width=0.6\textwidth]{background_menstrual_cycle_physiology}
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\caption{Physiological changes during the menstrual cycle\cite{pedroso_menstrual_2022}.}
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\label{fig:background_menstrual_cycle_physiology}
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\end{figure}
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Not every cycle results in ovulation—a phenomenon known as anovulation—which leads to a monophasic temperature pattern.
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Anovulation can have various causes, including hormonal imbalances, stress, or underlying health conditions\cite{rosenfield_adolescent_2013}.
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Anovulation is reflected in temperature data as either an absence of a clear temperature rise or a rise
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that is insufficient in magnitude or duration to be considered a reliable indicator of ovulation.
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Distinguishing between ovulatory and anovulatory cycles is challenging, as the only definitive confirmation of
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successful ovulation in a clinical sense is a positive pregnancy test.
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Even ultrasound imaging can only confirm that an egg was released from its follicle—not whether it was fertilized or successfully implanted.
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%TODO: find source for this
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%TODO: show plot of different cycle types
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\subsubsection{Fertility Prediction}\label{subsec:fertility_prediction}
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Throughout the menstrual cycle, the chance of fertilization varies significantly.
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An egg cell released from the ovary during ovulation, can be fertilized for up to 24 hours.
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@@ -56,7 +69,7 @@ as illustrated in Figure~\ref{fig:background_pregnancy_chance}.
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\begin{figure}
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\centering
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\includegraphics[width=0.8\textwidth]{background_pregnancy_chance_over_time}
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\includegraphics[width=0.7\textwidth]{background_pregnancy_chance_over_time}
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\caption{Chance of fertilization depending on the day of the menstrual cycle.
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The highest chance is around one day before ovulation\cite{dunson_day-specific_1999}.}
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\label{fig:background_pregnancy_chance}
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@@ -93,4 +106,5 @@ There are usually two main goals:
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understanding the underlying mechanisms that lead to the observed data and predicting future data points based on the
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historical information and potentially external factors\cite{cryer_time_2008}
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\\
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Time series analysis encompasses various methods, ranging from simple statistical models to complex deep learning architectures.
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Time series analysis encompasses various methods, ranging from simple statistical models to complex deep learning architectures.
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Classical methods
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