Abductive inference models for diagnostic problem-solving
Abductive inference models for diagnostic problem-solving
HYDI: a hybrid system with feedback for diagnosing multiple disorders
HYDI: a hybrid system with feedback for diagnosing multiple disorders
Inductive learning for abductive diagnosis
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Inductive Learning for Case-Based Diagnosis with Multiple Faults
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Case-Based Reasoning Technology, From Foundations to Applications
Extension of the HEPAR II Model to Multiple-Disorder Diagnosis
Proceedings of the IIS'2000 Symposium on Intelligent Information Systems
Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence)
Improved heterogeneous distance functions
Journal of Artificial Intelligence Research
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Multiple disorders are a daily problem in medical diagnosis and treatment, while most expert systems make an implicit assumption that only single disorder occurs in a single patient. In our paper, we show the need for performing multiple disorders diagnosis, and investigate a way of using inductive rules in our Case-based Reasoning System for diagnosing multiple disorder cases. We applied our approach to two medical casebases taken from real world applications demonstrating the promise of the research. The method also has the potential to be applied to other multiple fault domains, e.g. car failure diagnosis.