Cancer is the leading cause of death worldwide and research is being actively pursued by various organizations as well as cancer consortia in every country. In addition, interest in cancer treatment is increasing as we enter the era of “personalized medicine” where diseases are predicted and treated based on individual characteristics.

Recently, research combining big data and artificial intelligence is increasing. Accordingly, research related to artificial intelligence is being actively carried out in genome analysis. Many cancer-specific genes have been discovered using gene expression data.

However, there are limitations of high-dimensional gene expression data. As a solution to these limitations, there are various methods in the field of machine learning.

Therefore, unlike the analysis method that uses existing gene expression data, this study attempted to overcome the limitations of existing studies by applying it to the field of machine learning.

In other words, the goal was to apply the machine learning method to find a group of genes that can distinguish well between cancer and normal samples.

Keywords

Cancer, Personalized Medicine, Artificial Intelligence, Gene Expression and Machine Learning