Online Diagnostic System Based on Bayesian Networks
In this paper we present a general medical diagnostic expert system intended to serve as an educational self-diagnostic tool, openly available through the WWW. The system has been designed as an alternative to the common self-diagnosis practice among the general public of searching the Internet, finding the first disease with some matching symptoms, and treating this as a diagnosis, in contrast with the differential diagnosis offered by our system. We discuss the medical knowledge elicitation process, automated generation of Bayesian network models, and the diagnostic process. The system uses a scalable and efficient distributed reasoning engine based on multiple Bayesian networks. An analysis of over 100,000 diagnostic cases is presented. The cases are analyzed based on population characteristics such as age and gender. The results show the need for medical education and highlight the most common problems in non-emergency medical care.
KeywordsExpert systems Bayesian networks Computer-aided diagnosis
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- 3.Pearl, J.: Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann (1988)Google Scholar
- 4.Middleton, B., Shwe, M., Heckerman, D., Henrion, M., Horvitz, E., Lehmann, H., Cooper, G.: Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. Medicine 30, 241–255 (1991)Google Scholar
- 6.D’Ambrosio, B.: Symbolic probabilistic inference in large BN2O networks. In: Proc. Tenth Conf. on Uncertainty in Artificial Intelligence, pp. 128–135 (1994)Google Scholar
- 7.SMILE: Structural Modeling, Inference, and Learning Engine, http://genie.sis.pitt.edu