Making Sense of Large Scale Fertility Data [19N]

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Abstract

INTRODUCTION:

So far, the published data on menstrual cycle was collected by participants, through period diaries. This approach creates massive bottlenecks, where individuals with insufficient computing power can't process enough data for meaningful interpretation on a global scale. In addition, studies published so far are mostly geo specific. Today, with mobility on the increase, standardized charts made for each region are proving to be less precise, and sample size used in studies is too small to hold global claims. Moreover, most of the data representing landmark findings was collected over 4 decades ago. We aim to revise certain dogmatized values, such as menstrual cycle length and luteal phase length with carefully collected global datasets.

METHODS:

Mobile phone application Clue enables individuals to collect the data on the duration of menstrual cycle, the intensity and length of the bleeding, PMS and 22 more factors that may impact the cycle. Large set data analysis and comparisons are done at Clue.

RESULTS:

From the data analysis so far, a portion of our findings may confirm some of the previously published work on a larger population sample. Here, we will for the first time present our insights into the cycle length, duration of menstrual bleeding and accompanying factors (such as PMS) across age, lifestyles and populations worldwide.

CONCLUSION:

There is still no consensus on how big data should be used in female reproductive healthcare research. We are starting to understand complexity and the power of the data collected, and develop tools for creating actionable outputs (creating better predictions).

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