Wcn24-2142 Computational Methodology to Characterize and Identify Damage Patterns in Acute Kidney Injury Patients

The application of methods of artificial intelligence (AI) has been widely used in several fields, and recently it has resulted to be an essential tool to speed up the process of data analysis, diagnosis, and prediction for the study of diseases. In particular, determining the subphenotification of patients with acute kidney injury (AKI) has had an impact not only in handling large amounts of data but also because of the different types of data generated. In this respect, the development of computational methods aimed at resolving and proposing solution schemes that characterize clinical data for this multi-systemic syndrome is of great relevance.