TY - GEN
T1 - Multi-level interactive medical process mining
AU - Canensi, Luca
AU - Leonardi, Giorgio
AU - Montani, Stefania
AU - Terenziani, Paolo
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - In this paper, we present a novel process mining approach, specifically tailored to medical applications, which allows the user to build an initial process model from the hospital event log, and then supports further model refinements, by directly exploiting her knowledge-based model evaluation. In such a way, it supports the interactive construction of the process model at multiple and user-defined levels of abstraction, ranging from a model which perfectly adheres to the input traces (i.e., all of its paths correspond to at least one trace in the log) to models which increasingly loose precision, but gain generality. Our results in the field of stroke management, reported as a case study in this paper, show that our approach can provide relevant advantages with respect to traditional process mining techniques.
AB - In this paper, we present a novel process mining approach, specifically tailored to medical applications, which allows the user to build an initial process model from the hospital event log, and then supports further model refinements, by directly exploiting her knowledge-based model evaluation. In such a way, it supports the interactive construction of the process model at multiple and user-defined levels of abstraction, ranging from a model which perfectly adheres to the input traces (i.e., all of its paths correspond to at least one trace in the log) to models which increasingly loose precision, but gain generality. Our results in the field of stroke management, reported as a case study in this paper, show that our approach can provide relevant advantages with respect to traditional process mining techniques.
UR - http://www.scopus.com/inward/record.url?scp=85021634818&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-59758-4_28
DO - 10.1007/978-3-319-59758-4_28
M3 - Conference contribution
AN - SCOPUS:85021634818
SN - 9783319597577
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 256
EP - 260
BT - Artificial Intelligence in Medicine - 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Proceedings
A2 - [surname]ten Teije, Annette
A2 - Popow, Christian
A2 - Sacchi, Lucia
A2 - Holmes, John H.
PB - Springer Verlag
T2 - 16th Conference on Artificial Intelligence in Medicine, AIME 2017
Y2 - 21 June 2017 through 24 June 2017
ER -