Abstract
Accuracy and reliability are major concerns for the developers of expert systems. We have developed a Bayesian expert system for medicine, Iliad. We have included in Iliad new types of decision frames, called clusters. Clusters are frames (usually Boolean) that contain groups of conditionally dependent findings. These groups often describe pathophysiologic concepts.
Because clusters encapsulate groups of conditionally dependent findings, we expected clusters might increase Iliad's accuracy and reliability. We tested this hypothesis by measuring the reliability of pairs of clustered and nonclustered frames using real patient data.
Full text
PDF
Selected References
These references are in PubMed. This may not be the complete list of references from this article.
- Habbema J. D., Hilden J., Bjerregaard B. The measurement of performance in probabilistic diagnosis. I. The problem, descriptive tools, and measures based on classification matrices. Methods Inf Med. 1978 Oct;17(4):217–226. [PubMed] [Google Scholar]
- Hilden J., Habbema J. D., Bjerregaard B. The measurement of performance in probabilistic diagnosis. II. Trustworthiness of the exact values of the diagnostic probabilities. Methods Inf Med. 1978 Oct;17(4):227–237. [PubMed] [Google Scholar]
- Rifkin R. D. Maximum Shannon information content of diagnostic medical testing. Including application to multiple non-independent tests. Med Decis Making. 1985 Summer;5(2):179–190. doi: 10.1177/0272989X8500500207. [DOI] [PubMed] [Google Scholar]