Exemplar based knowledge acquisition: a unified approach to concept representati on, classification, and learning
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Experiences with Case-Based Reasoning Methods and Prototypes for Medical Knowledge-Based Systems
AIMDM '99 Proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
Retrieving Adaptable Cases: The Role of Adaptation Knowledge in Case Retrieval
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
Retrieval in a Prototype-Based Case Library: A Case Study in Diabetes Therapy Revision
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Modelling the Competence of Case-Bases
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Diagnosis and Decision Support
Case-Based Reasoning Technology, From Foundations to Applications
MacRad: Radiology Image Resource with a Case-Based Retrieval System
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
Rapid retrieval algorithms for case-based reasoning
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Acquiring Adaptation Knowledge for CBR with MIKAS
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Building a case-based diet recommendation system without a knowledge engineer
Artificial Intelligence in Medicine
| Hi-index | 0.00 |
For an intensive care unit, we have developed an antibiotics therapy advice system, called ICONS. To speed-up the process of finding suitable therapy recommendations we have applied Case-based Reasoning techniques. As in a medical expert system all required information should always be up-to-date, a static case base is inappropriate. New cases should be incrementally incorporated into the case base and outdated ones should be updated or erased. For reasons of space limitations and of retrieval time an indefinite growth of the case base should be avoided. To fulfil these requirements we propose to generalise from single cases to prototypical cases and to erase redundant cases. In this paper, we mainly focus on results of extended experiments with generation strategies of generalised cases (prototypes). Additionally, we compare measured retrieval times for two indexing retrieval algorithms: For simple indexing and Tree-Hash retrieval.