Paper Info
Title
Prototypical case mining from biomedical literature for bootstrapping a case base
Abstract
This article addresses the task of mining for cases from biomedical literature to automatically build an initial case base for a case-based reasoning (CBR) system. This research takes place within the Mémoire project, which has for goal to provide a framework to facilitate building CBR systems in biology and medicine. By analyzing medical literature, the ProCaseMiner system mines for medical concepts such as diseases, signs and symptoms, laboratory tests, and treatment plans in relationship with one another, and connects them together in a given medical domain. It then organizes these concepts in a higher-level structure called a case. This case mining component provides a definite help to bootstrap the creation of a biomedical CBR system case base, composed of both concrete cases and prototypical cases. Currently, most cases learnt correspond to prototypical cases, given the level of abstraction of their features. This article validates the approach by presenting a comparison between the prototypical cases learnt from stem-cell transplantation domain with those created by a team of experts in the domain.
Year
DOI
Venue
2008
https://doi.org/10.1007/s10489-007-0061-3
Applied Intelligence
Keywords
Field
DocType
Medical case-based reasoning,Case-based reasoning,Medical informatics,Text mining,Case mining
Data science,Abstraction,Bootstrapping,Computer science,Case base,Artificial intelligence,Health informatics,Case-based reasoning,Transplantation,Machine learning,Medical literature
Journal
Volume
Issue
ISSN
28
3
0924-669X
Citations 
PageRank 
References 
9
0.52
31
Authors
1
Name
Order
Citations
PageRank
Isabelle Bichindaritz153255.74