@inproceedings{419ac82aeb1e47d4841755fd02e73fdd,
title = "Probabilistic diagnostic reasoning: towards improving diagnostic efficiency",
abstract = "This paper describes a new approximation method which can significantly improve the computational efficiency of Bayesian Networks. We apply this technique to the diagnosis of acute abdominal pain, with good results. This approach is based on using a reduced set of the model parameters for diagnostic reasoning. The tradeoffs in diagnostic accuracy required to obtain increased computational efficiency (due to the smaller models) are carefully specified using a variety of statistical metrics.",
author = "Provan, \{Gregory M.\}",
year = "1994",
language = "English",
isbn = "081865550X",
series = "Proceedings of the Conference on Artificial Intelligence Applications",
publisher = "Publ by IEEE",
pages = "441--447",
booktitle = "Proceedings of the Conference on Artificial Intelligence Applications",
note = "Proceedings of the 10th Conference on Artificial Intelligence for Applications ; Conference date: 01-03-1994 Through 04-03-1994",
}