Modelling a decision-support system for oncology using rule-based and case-based reasoning methodologies.
In most hospital medical units, multidisciplinary committees meet weekly to discuss their patients' cases. The medical experts base their decisions on three sources of information. First, they check if their patient complies with existing guidelines. Failing these, the medical experts will base their therapeutic decisions on the cases of similar patients that they have treated in the past. We propose a multi-modal reasoning decision-support system based on both guideline and case series, which will automatically compare the patient's case to the corresponding guideline, then to other cases, and retrieve similar cases. The general structure of the system is presented here, the domain of application being oncology. As the patients' records are not currently stored in a database in a format which is directly accessible, an object-oriented model is proposed, which includes prognosis factors currently tested in clinical trials, well-established ones, and a description of the illness episodes. The system is designed to be a data warehouse. Such a system does not exist in the literature. Future work will be needed to define the similarity measures, and to connect the system to the current database.