Abstract
Problem statement: The Case Based Reasoning (CBR) method can be implemented in differential diagnosis analysis. C4.5 algorithm has been commonly used to help the method's knowledge building process. This process is completed by constructing decision tree from previously handled cases data. The C4.5 algorithm itself can be used with an assumption that all the cases has an exact and equal truth value thus have an exact contribution in decision tree building process. However, the decision makers sometimes not sure about the truth of the cases in the cases database, therefore the confidence value can be different for case by case. Besides that, the C4.5 algorithm can only handle cases that are stored in a flat table with data in form of categorized text or in discrete class. This algorithm has not yet explained about how is decision tree building mechanism in situation when the data are stored in relational tables. It also has not yet explained about the process of knowledge building when the data are in the form of number in continuous class. Meanwhile, the observed objects in this research, that is medical record data, are mostly stored in a complex relational database and have common form of categorized text, discrete number, continuous number and image. Therefore, the C4.5 is needed to be improved so it can handle decision building for cases database of medical record. Approach: We develop a knowledge building framework that can handle confidence level difference of cases in cases database. The framework we build also allows the data are stored in relational database. Moreover, our framework can process data in the form of categorized text, discrete number, continuous number and image. This framework is named CUC-C4.5, abbreviated from Complex Uncertain Case C4.5 as it is the improvement from C4.5 algorithm. Results: The CUC-C4.5 framework has been applied on the case of differential diagnosis knowledge building in a group decision support system to handle geriatric patient. This framework was implemented by using PHP and Javascript programming language and MySQL DBMS. Conclusion: The CUC-C4.5 can support differential diagnosis analysis on group decision support system for geriatric assessment.
Highlights
Case Based Reasoning (CBR) method allows making analysis or reasoning for a case based on previous experiences
Abidi (2002) has made a research about the use of CBR to manage people’s personal health dynamically. He implemented it in a Java-based case based reasoning engine that applied a compositional adaptation algorithm to a personal health information package in HTML format that can be sent to user’s email
Selected variable data are defined as variable data that are selected by decision makers as determinant variable
Summary
Case Based Reasoning (CBR) method allows making analysis or reasoning for a case based on previous experiences. Every possibility of diseases for a patient (differential diagnosis) can be analyzed by using medical record data as the cases database. Abidi (2002) has made a research about the use of CBR to manage people’s personal health dynamically. He implemented it in a Java-based case based reasoning engine that applied a compositional adaptation algorithm to a personal health information package in HTML format that can be sent to user’s email. Another application in clinical was implemented by Salam Khan (2003) for diet recommendation
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