T-CARE: temporal case retrieval system

The temporal dimension is highly present in almost all critical medical scenarios (e.g. intensive care units, burn units or cardiology departments), considering that the temporal evolution of the patient is a key factor in providing an effective healthcare. While the irruption of new technologies in hospital services provides large amounts of data, knowledge-based systems are not often considered by clinicians, as part of the clinical information process. Case-based reasoning (CBR) is a field of artificial intelligence that tackles new problems by referring to analogous problems that have already been solved in the past. Therefore, CBR seems to be an effective approach in medical domains since cases refer directly to patient episodes within the health records. Despite the importance of the temporal dimension, no in-depth study of the impact of time on the CBR systems has been carried out in critical medical domains. This work focuses on the development of case retrieval systems based on their temporal similarity in the medical domain. We present T-CARE, a temporal case retrieval system that combines classical and non-classical approaches to measure temporal similarity of cases which are composed of temporal sequences of time point events and intervals. Finally, we show its practical implementation in an intensive care burn unit.