Paper Info
Title
Study Of Similarity Measures For Case-Based Reasoning In Transcatheter Aortic Valve Implantation
Abstract
Case-Based Reasoning (CBR) uses previous experiences to solve similar current problems. The basic hypothesis is that similar cases should have similar solutions. In the case of Transcatheter Aortic Valve Implantation (TAVI), the CBR could help practitioners to plan the procedure. Four steps compose a CBR: retrieve, reuse, revise and retain. Defining a convenient similarity measure (SM) is essential in the retrieve step. This study aims to analyze the performance of different similarity measures and attribute selections. Generally in the retrieve step, a standard weighted heterogeneous similarity measure (WHSM) is used, in association with the k-nearest neighbor algorithm. Based on WHSM, we considered new definitions of SMs dedicated to decision support for TAVI. They include attributes selection and weight determination through a clinical decision tree. The performance of SMs was evaluated on a set of 100 cases with a leave-one-out cross validation. Results show that the CBR retrieving process can be improved by using dedicated SMs.
Year
DOI
Venue
2017
10.22489/CinC.2017.134-299
2017 COMPUTING IN CARDIOLOGY (CINC)
Field
DocType
Volume
Decision tree,Similarity measure,Reuse,Computer science,Decision support system,Aortic valve,Artificial intelligence,Case-based reasoning,Cross-validation,Machine learning
Conference
44
ISSN
Citations 
PageRank 
2325-8861
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Hélène Feuillâtre100.34
Vincent Auffret261.52
Miguel Castro343.22
Hervé Le Breton400.68
Mireille Garreau532.82
Pascal Haigron65713.53