Data science

Our group combines big data resources such as electronic medical records, genetics and eHealth collection, with high throughput computational methods in order to identify homogeneous patterns of rheumatic diseases. For this we employ machine learning methods to optimize disease classification, natural language processing to transform real world data into scientific data and clustering analysis to discern latent structure in situations where dependent and independent variables are uncertain.