Authors:
Rainer Schmidt
1
and
Olga Vorobieva
2
Affiliations:
1
Institute for Medical Informatics and Biometry, University of Rostock, Germany
;
2
Institute for Medical Informatics and Biometry, University of Rostock; Sechenov Institute of Evolutionary Physiology and Biochemistry, Russian Federation
Keyword(s):
Case-Based Reasoning, Medicine, Exceptional Cases.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Case-Based Reasoning
;
Enterprise Information Systems
;
Pattern Recognition
;
Symbolic Systems
;
Theory and Methods
;
Verification and Validation of Knowledge-Based Systems
Abstract:
In medicine many exceptions occur. In medical practice and in knowledge-based systems too, it is necessary to consider them and to deal with them appropriately. In medical studies and in research, exceptions shall be explained. We present a system that helps to explain cases that do not fit into a theoretical hypothesis. Our starting points are situations where neither a well-developed theory nor reliable knowledge nor a case base is available at the beginning. So, instead of reliable theoretical knowledge and intelligent experience, we have just some theoretical hypothesis and a set of measurements. In this paper, we propose to combine Case-Based Reasoning with a statistical model. We use Case-Based Reasoning to explain those cases that do not fit the model. The case base has to be set up incrementally, it contains the exceptional cases, and their explanations are the solutions, which can be used to help to explain further exceptional cases.