TY - CHAP
T1 - Non-exhaustive trace retrieval for managing stroke patients
AU - Montani, S.
AU - Leonardi, G.
PY - 2014
Y1 - 2014
N2 - Retrieving and inspecting traces that log medical processes execution can be a significant help in exception management, and is the first step towards a thorough analysis of the service provided by an health care organization. In this work, we report on extensive retrieval experiments, conducted on a database of 2000 real patient traces, collected at different stroke management units in the Lombardia region, Italy. In our approach, retrieval exploits a K-Nearest Neighbor technique, and relies on a distance definition able to explicitly take into account temporal information in traces-since in emergency medicine the role of time is central. Retrieval is also made faster by the application of non-exhaustive search procedures, that are described in the paper.
AB - Retrieving and inspecting traces that log medical processes execution can be a significant help in exception management, and is the first step towards a thorough analysis of the service provided by an health care organization. In this work, we report on extensive retrieval experiments, conducted on a database of 2000 real patient traces, collected at different stroke management units in the Lombardia region, Italy. In our approach, retrieval exploits a K-Nearest Neighbor technique, and relies on a distance definition able to explicitly take into account temporal information in traces-since in emergency medicine the role of time is central. Retrieval is also made faster by the application of non-exhaustive search procedures, that are described in the paper.
UR - http://www.scopus.com/inward/record.url?scp=84884196061&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-38736-4_3
DO - 10.1007/978-3-642-38736-4_3
M3 - Chapter
SN - 9783642387357
T3 - Studies in Computational Intelligence
SP - 29
EP - 42
BT - Successful Case-Based Reasoning Applications-2
A2 - Montani, Stefania
A2 - Jain, Lakhmi
ER -