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Machine Learning in Period, Fertility and Ovulation Tracking Application
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  • Tanmay Thakur ,
  • Saurabh Kadam ,
  • Nikita Patil ,
  • Chinmayee Achrekar
Tanmay Thakur
Vasantdada Patil Prathisthans College of Engineering and Visual Arts

Corresponding Author:[email protected]

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Saurabh Kadam
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Nikita Patil
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Chinmayee Achrekar
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Machine learning has the potential to improve the accuracy of period tracking applications by analyzing patterns in menstrual cycle data. The ability to predict the timing of menstrual cycles is important for women's health, and can be used to provide personalized reminders and notifications, as well as to better understand and manage menstrual cycles.