Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Case-Based Reasoning in the Care of Alzheimer's Disease Patients
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Microarray gene expression data association rules mining based on BSC-tree and FIS-tree
Data & Knowledge Engineering - Special issue: Biological data management
Integrating data mining with case-based reasoning for chronic diseases prognosis and diagnosis
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Two-step filtering datamining method integrating case-based reasoning and rule induction
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Case-based reasoning in the health sciences: What's next?
Artificial Intelligence in Medicine
Computer Methods and Programs in Biomedicine
How to combine CBR and RBR for diagnosing multiple medical disorder cases
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Artificial Intelligence in Medicine
Hybrid knowledge-based systems for therapy planning
Artificial Intelligence in Medicine
Mining medical specialist billing patterns for health service management
AusDM '08 Proceedings of the 7th Australasian Data Mining Conference - Volume 87
Proposing a Business Model in Healthcare Industry: E-Diagnosis
International Journal of Healthcare Information Systems and Informatics
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Prescription is an important element in the medical practice. An appropriate drug therapy is complex in which the decision of prescribing is influenced by many factors. Any discrepancy in the prescription making process can lead to serious consequences. In particular, the General Practitioners (GPs), who need to diagnose and treat a wide range of health conditions and diseases, must be knowledgeable enough in deciding what type of medicines should be given to the patients. With the widespread computerization of medical records, GPs now can make use of accumulated historic clinical data in retrieving similar decisions in therapeutic treatment for treating the new situation. However, the applications of decision support tools are rarely found in the prescription domain due to the complex nature of the domain and limitations of the existing tools. It was argued that existing tools can only solve a small amount of the cases on the real world dataset. This paper proposes a new revised Case-based Reasoning (CBR) mechanism, named Rule-Associated CasE-based Reasoning (RACER), which integrates CBR and association rules mining for supporting GPs prescription. It aims at leveraging the two most common techniques in the field and dealing with the complex multiple values solution. Eight hundred real cases from a medical organization are collected and used for evaluating the performance of RACER. The proposed method was also compared with CBR and association rules mining for testing. The results demonstrate that the combination leads to increased in both recall and precision in various settings of parameters. The performance of RACER remains stable by using different sets of parameters, which shows that the most important element of the mechanism is self-determined.