Predicting the Evolution of Cancer Stem Cell Subtypes Using a Machine Learning Framework
摘要
Cancer stem cells (CSCs) are subpopulation of cells in a tumor that are very important for analysis and treatment in clinical practice. The aim of this study is the use of Machine learning (ML) methodology to predict the development of CSCs subpopulation in colon and breast cancer cells. Input data for training Genetic algorithm (GA) and fitting was used from experimental measurements on flow cytometry of CSCs surface markers expression in cancer cells. Based on the results, GA prediction model has archived high accuracy in estimating the expression rate of CSCs markers on cancer cells. Artificial intelligence can be used as a powerful tool for predicting of behavior of cancer stem cell subpopulation.