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Abstract: A major part of the knowledge in the medical field concerns diseases that are uncommon or even rare. Doctors, however, may face severe difficulties in handling such disorders, as they may not have sufficient experience with the management of these disorders in patients. Here there seems to be a clear role for medical decision-support systems. Unfortunately, the uncommon nature of these disorders renders it almost impossible to collect data from a sufficiently large number of patients as... (Update)
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BibTeX entry: (Update)
@misc{ lucas-enhancement,
author = "Peter Lucas",
title = "Enhancement of Learning by Declarative Expert-based Models",
url = "citeseer.ist.psu.edu/398721.html" }
Citations (may not include all citations):976 Machine Learning (context) - Mitchell - 1997
760 Probabilistic Reasoning in Intelligent Systems (context) - Pearl - 1988
582 Local computations with probabilities on graphical structure.. (context) - Lauritzen, Spiegelhalter - 1987
416 A Bayesian method for the induction of probabilistic network.. (context) - Cooper, Herskovitz - 1992
351 Learning Bayesian networks: the combination of knowledge and.. - Heckerman, Geiger et al. - 1995
36 Principles of Expert Systems (context) - Lucas, van der Gaag - 1991
28 The sensitivity of belief networks to imprecise probabilitie.. - Pradhan, Henrion et al. - 1996
16 Medical Decision Making (context) - Sox, Blatt et al. - 1988
16 Computer-based decisionsupport in the management of primary .. - Lucas, Boot et al. - 1998
14 Sequential model criticism in probabilistic expert systems (context) - Cowell, Dawid et al. - 1993
3 Bayesian Knowledge Discoverer: reference manual (context) - Ramoni, Sebastiani - 1997
3 Learning logic programs with structured background knowledge (context) - Horv, Turv - 1996
3 Ecient Parameter Learning in Bayesian Networks from Incomple.. (context) - Ramoni, Sebastiani - 1997
2 An introduction to the Robust Bayesian Classier (context) - Ramoni, Sebastiani - 1999
2 Robust outcome prediction for intensive-care patients - Ramoni, Sebastiani et al. - 1999
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