Adding features from the mathematical model of breast cancer to predict the tumour size
Ophir Nave · International Journal of Computer Mathematics Computer Systems Theory · 2020
In this study, we combine a theoretical mathematical model with machine learning (ML) to predict tumour sizes in breast cancer. Our study is based on clinical data from 1869 women of various ages with breast cancer. To accurately predict tumour size for each woman individually, we solved our customized mathematical model for each woman, then added the solution vector of the dynamic variables in the model (in machine learning language, these are called features) to the clinical data and used a variety of machine learning algorithms. We compared the results obtained with and without the mathematical model and showed that by adding specific features from the mathematical model we were able to better predict tumour size for each woman.