Machine learning analysis of a Chilean breast cancer registry

Abstract

In recent years, artificial intelligence (AI) and machine learning (a form of AI) have offered valuable tools for medicine by applying and training algorithms in order to make predictions. Herein, we applied a machine learning algorithm to analyze data from a >20 year breast cancer (BC) registry elaborated in two Chilean health institutions (a public hospital and a private center) that includes a total of 4838 patients and their basic clinicalpathological characteristics. Preliminary results suggest that this cohort of patients can be subdivided into five clusters according to key variables that also correlate with overall survival and disease-free survival rates. To our knowledge this is the first Latin American report of its kind. Our laboratory is currently expanding these analyses.