On Test Selection Strategies for Belief Networks

Decision making under uncertainty typically requires an iterative process of information acquisition. At each stage, the decision maker chooses the next best test (or tests) to perform, and re-evaluates the possible decisions. Value-of-information analyses provide a formal strategy for selecting the next test(s). However, the complete decision-theoretic approach is impractical and researchers have sought approximations.

[1]  Finn Verner Jensen,et al.  dr-Hugin: A System for Hypothesis Driven Data Request , 1995 .

[2]  Shili Lin,et al.  ON THE PERFORMANCE OF MARKOV CHAIN MONTE CARLO METHODS ON PEDIGREE DATA AND A NEW ALGORITHM , 1992 .

[3]  R. M. Oliver,et al.  Influence diagrams, belief nets and decision analysis , 1992 .

[4]  R. G. Almond,et al.  Lack-of-information-based control in graphical belief systems , 1993 .

[5]  D. Heckerman,et al.  Toward Normative Expert Systems: Part I The Pathfinder Project , 1992, Methods of Information in Medicine.

[6]  Wray L. Buntine Operations for Learning with Graphical Models , 1994, J. Artif. Intell. Res..

[7]  D. J. Spiegelhalter,et al.  Statistical and Knowledge‐Based Approaches to Clinical Decision‐Support Systems, with an Application in Gastroenterology , 1984 .

[8]  L. N. Kanal,et al.  Uncertainty in Artificial Intelligence 5 , 1990 .

[9]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .

[10]  R. Detrano,et al.  International application of a new probability algorithm for the diagnosis of coronary artery disease. , 1989, The American journal of cardiology.

[11]  Charles J. Geyer,et al.  Practical Markov Chain Monte Carlo , 1992 .

[12]  G. P. Vogler,et al.  Efficient methods for computing linkage likelihoods of recessive diseases in inbred pedigrees , 1991, Genetic epidemiology.

[13]  Prakash P. Shenoy,et al.  Axioms for probability and belief-function proagation , 1990, UAI.

[14]  D M McSherry Intelligent dialogue based on statistical models of clinical decision-making. , 1986, Statistics in medicine.

[15]  Perry L. Miller,et al.  ATTENDING: Critiquing a Physician's Management Plan , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  D. J. Hand,et al.  Artificial Intelligence Frontiers in Statistics: AI and Statistics III , 1992 .

[17]  Moshe Ben-Bassat,et al.  Myopic Policies in Sequential Classification , 1978, IEEE Transactions on Computers.

[18]  A. Raftery,et al.  How Many Iterations in the Gibbs Sampler , 1991 .

[19]  I. Good,et al.  The Diagnostic Process with Special Reference to Errors , 1971, Methods of Information in Medicine.

[20]  Barr and Feigenbaum Edward A. Avron,et al.  The Handbook of Artificial Intelligence , 1981 .

[21]  Eric Horvitz,et al.  An Approximate Nonmyopic Computation for Value of Information , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  A. P. Dawid,et al.  Applications of a general propagation algorithm for probabilistic expert systems , 1992 .

[23]  P Glasziou,et al.  Test Selection Measures , 1989, Medical decision making : an international journal of the Society for Medical Decision Making.