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
M | Day | Year | Period |
---|---|---|---|
6 | 30 | 20XX | Starts |
7 | 1 | 20XX | Ends |
Rosana Rego. 2023. Predictive Modeling of Menstrual Cycle Length: A Time Series Forecasting Approach, PREPRINT (Version 1) available at Research Square.