Learning in large relational databases with an application in intensive care medicine.

The project aims at the elaboration of inductive logic programming and stochastic relational learning techniques to make them better suited for data mining in large relational databases. The focus is on scalability issues. The application domain is data collected by the continuous monitoring of patients in an intensive care unit. In the application domain, the aim is to discovers patterns that help internists in predicting the evolution of patients.

Keywords:machine learning, data mining, intensive care, patient data management system

Disciplines:Artificial intelligence, Cognitive science and intelligent systems, Applied mathematics in specific fields