Time Series Forecasting Approach based on Artificial intelligence implementation for better cycle predictions.

The period can be uncertain when a woman has irregular cycles. Moreover, the length of the period cycle varies from woman to woman. Therefore, every woman has a particular cycle. AI can help us to understand better about women cycles.

In this project, we applied some machine learning models to predict the period cycle. We generated a synthetic dataset.

What things you need to have to be able to run:

• Python 3.6 +
• Pip 3+
• VirtualEnvWrapper is recommended but not mandatory

$ pip install -r requirements.txt

The format of the data file .csv should be

Rosana Rego. 2023. Predictive Modeling of Menstrual Cycle Length: A Time Series Forecasting Approach, PREPRINT (Version 1) available at Research Square.