Artificial Intelligence Review - Special issue on lazy learning
Genetic Algorithms to Optimise CBR Retrieval
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Building CBR systems with jcolibri
Science of Computer Programming
GerAmi: Improving Healthcare Delivery in Geriatric Residences
IEEE Intelligent Systems
Case-Based Decision Support for Patients with Type 1 Diabetes on Insulin Pump Therapy
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Rapid Prototyping of CBR Applications with the Open Source Tool myCBR
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Case-based reasoning in the health sciences: What's next?
Artificial Intelligence in Medicine
Case-based object recognition for airborne fungi recognition
Artificial Intelligence in Medicine
Guest Editorial: Advances in case-based reasoning in the health sciences
Artificial Intelligence in Medicine
MedCase: a template medical case store for case-based reasoning in medical decision support
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Electronic patient records (EPRs) contain a wealth of patient-related data and capture clinical problem-solving experiences and decisions. Excelicare is such a system which is also a platform for the national generic clinical system in the UK. Objective: This paper presents, ExcelicareCBR, a case-based reasoning (CBR) system which has been developed to complement Excelicare. Objective of this work is to integrate CBR to support clinical decision making by harnessing electronic patient records for clinical experience reuse. Methods: CBR is a proven problem solving methodology in which past solutions are reused to solve new problems. A key challenge that we address in this paper is how to extract and represent a case from an EPR. Using an example from the lung cancer domain we demonstrate our generic case representation approach where Excelicare fields are mapped to case features. Once the case base is populated with cases containing data from the EPRs database a standard weighted k-nearest neighbour algorithm combined with a genetic algorithm based feature weighting mechanism is used for case retrieval and reuse. Conclusions: We conclude that incorporating case authoring functionality and a generic retrieval mechanism were key to successful integration of ExcelicareCBR. This paper also demonstrates how the application of CBR can enable sharing of lessons learned through the retrieval and reuse of EPRs captured as cases in a case base.