Bayesian Net References
Version 4
13 July 2008
This document contains a list of references to publications and reports about Bayesian Net technology, and especially Bayesian Net applications. The report will be regularly updated and we welcome suggestions for new references to be added. Please send new references for inclusion to norman@agenarisk.com
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AbdelHamid, T. K. (1996). The slippery path to productivity improvement. IEEE Software, 13(4), 4352 Abderrahim, D., L. Bernard, et al. (2006). TIDES  Using Bayesian Networks for Student Modeling. Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies, IEEE Computer Society: 1002  1007 Abramson, B. (1994). "The design of belief networkbased systems for price forecasting." Computers & Electrical Engineering 20(2): 163180 Abramson, B., J. Brown, et al. (1996). "HAILFINDER: A Bayesian system for predicting extreme weather." International Journal of Forecasting 7: 5778 Ackerman, F. and C. Eden (2005). "Using Causal Mapping with Group Support Systems to Elicit an Understanding of Failure in Complex Projects: Some Implications for Organizational Research." Group Decision and Negotiation 14: 355–376 Ackermann, F., C. Eden, et al. (1997). "Modeling for Litigation: Mixing Qualitative and Quantitative Approaches." Interfaces 27: 4865 Aires, F., C. Prigent, et al. (2004). "Neural network uncertainty assessment using Bayesian statistics: a remote sensing application." Neural Comput 16(11): 241558 Aitken, C. (1996). "Lies, damned lies and expert witnesses." Mathematics Today (Bulletin of the IMA) 32(5/6): 7680 Aitken, C., F. Taroni, et al. (2003). "A graphical model for the evaluation of crosstransfer evidence in DNA profiles." Theoretical Population Biology 63: 179190 Aitken, C. G. G. (2004 ). Statistical interpretation of evidence: Bayesian analysis, Joseph Bell Centre for Forensic Statistics & Legal Reasoning http://www.cfslr.ed.ac.uk/publications/a001.pdf. Aitken, C. G. G., T. Connolly, et al. (1995). Bayesian belief networks with an application in specific case analysis. Computational Learning and Probabilistic Reasoning. A. Gammerman, John Wiley and Sons Ltd. Aitken, C. G. G., T. Connolly, et al. (1996). "Statistical modelling in specific case analysis." Science & Justice: 36(4): 245255 Aktaşa, E., F. Ülengin, et al. (2007). "A decision support system to improve the efficiency of resource allocation in healthcare management." SocioEconomic Planning Sciences 41(2): 130146 Aliferis, C. F. and G. F. Cooper (1996). An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Using Simulated Data Sets. Section of Medical Informatics & Intelligent Systems Program,University of Pittsburg Aliferis, C. F. and G. F. Cooper (1996). A Structurally and Temporally Extended Bayesian Belief Network Model: Definitions, Properties, and Modelling Techniques. cons@smi.med.pitt.edu Alterovitz, G., M. Xiang, et al. (2007). "GO PaD: the Gene Ontology Partition Database." Nucleic Acids Res 35(Database issue): 3227 Alvarez, S. M., B. A. Poelstra, et al. (2006). "Evaluation of a Bayesian decision network for diagnosing pyloric stenosis." J Pediatr Surg 41(1): 15561; discussion 15561 Amasaki, S., O. Mizuno, et al. (2003). A Bayesian Belief Network for Predicting Residual Faults in Software Products. Proceedings of 14th International Symposium on Software Reliability Engineering (ISSRE2003), November, pp. 21522 An, X., D. Jutla, et al. (2006). Privacy intrusion detection using dynamic Bayesian networks. Proceedings of the 8th international conference on Electronic commerce: The new ecommerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet. Fredericton, New Brunswick, Canada, ACM: 208  215 Anderson, S. K., K. G. Olesen, et al. (2000). HUGIN  a shell for building Bayesian belief universes for expert systems. 11th Intl Joint Conf Artifical Intelligence. Detroit: 10801085 Andreassen, M. Woldbye, et al. (1987). MUNIN: a causal probabilistic network for interpretation of electromyographic findings. 10th International Joint Conference on Artificial Intelligence. Milan, Italy: 366372 Andreassen, S., F. Jensen, et al. (1991). "Medical expert systems based on causal probabilistic networks." Int J Biomed Comput 28(12): 130 Andreassen, S., C. Riekehr, et al. (1999). "Using probabilistic and decisiontheoretic methods in treatment and prognosis modeling." Artif Intell Med 15(2): 12134 Antal, P., G. Fannes, et al. (2003). "Bayesian applications of belief networks and multilayer perceptrons for ovarian tumor classification with rejection." Artif Intell Med 29(12): 3960 Antal, P., G. Fannes, et al. (2004). "Using literature and data to learn Bayesian networks as clinical models of ovarian tumors." Artif Intell Med 30(3): 25781 Arens, D. A. (1982). "Widowhood and wellbeing: an examination of sex differences within a causal model." Int J Aging Hum Dev 15(1): 2740 Aronsky, D., M. Fiszman, et al. (2001). "Combining decision support methodologies to diagnose pneumonia." Proc AMIA Symp: 126 Aronsky, D. and P. J. Haug (1998). "Diagnosing communityacquired pneumonia with a Bayesian network." Proc AMIA Symp: 6326 Aronsky, D. and P. J. Haug (2000). "Automatic identification of patients eligible for a pneumonia guideline." Proc AMIA Symp: 126 Astakhov, V. and A. Cherkasov (2005). "Prediction of HLAA2 binding peptides using Bayesian network." Bioinformation 1(2): 5863 Athanasiou, M. and J. Y. Clark (2007). A Bayesian Network Model for the Diagnosis of the Caring Procedure for Wheelchair Users with Spinal Injury. Twentieth IEEE International Symposium on ComputerBased Medical Systems (CBMS'07) 433438 Bacon, P. J., J. D. Cain, et al. (2002). "Belief network models of land manager decisions and land use change." Journal of Environmental Management 65(1): 123 Bahrami, H. (2006). "Causal models in primary open angle glaucoma." Ophthalmic Epidemiol 13(4): 2918 Bai, C.G. (2005). "Bayesian network based software reliability prediction with an operational profile." J. Syst. Softw. 77(2): 103112 Bai, C. G., Q. P. Hu, et al. (2005). "Software failure prediction based on a Markov Bayesian network model." J. Syst. Softw. 74(3): 275282 Baker, M. (2000). Diagnostic system utilizing a Bayesian network model having link weights updated experimentally. Patent number: 6076083 Bang, J. W. and D. Gillies (2002). Using Bayesian Networks to Model the Prognosis of Hepatitis C. In 7th Workshop on Intelligent Data Analysis in Medicine and Pharmacology, pages 7.15, Lyon, France Bang, J. W. and D. Gillies (2002). Using Bayesian Networks with Hidden Nodes to Recognise Neural Cell Morphology. In M. Ishizuka and A. Satter, editors, 7th Pacific Rim International Conference on Arti_cial Intelligence, pages 385.394, Tokyo, New York,. Springer Bangsø, O. and P. H. Wuillemin (2000). Topdown construction and repetitive structures representation in Bayesian networks. Proceedings of The Thirteenth International Florida Artificial Intelligence Research Symposium Conference. Florida, USA: 282286 Barahona, P. (1994). "A causal and temporal reasoning model and its use in drug therapy applications." Artif Intell Med 6(1): 127 Barker, G. C. (2004). Application of Bayesian Belief Network models to food safety science Batchelor, C. and J. Cain (1999). "Application of belief networks to water management studies." Agricultural Water Management 40(1): 5157 Bate, A. (2007). "Bayesian confidence propagation neural network." Drug Saf 30(7): 6235 Bate, A., M. Lindquist, et al. (1998). "A Bayesian neural network method for adverse drug reaction signal generation." Eur J Clin Pharmacol 54(4): 31521 Bate, A., M. Lindquist, et al. (2002). "A data mining approach for signal detection and analysis." Drug Saf 25(6): 3937 Bate, A., M. Lindquist, et al. (2002). "Datamining analyses of pharmacovigilance signals in relation to relevant comparison drugs." Eur J Clin Pharmacol 58(7): 48390 Bauer, E., D. Koller, et al. (1997). Update rules for parameter estimation in Bayesian networks. In Geiger D. and Shenoy P. (Eds.) Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, Morgan Kaufmann Publishers Inc., San Francisco, pp. 313 Bayesware. (2007). "Bayesware Knowledge Discovery by Bayesian Networks." http://www.bayesware.com/. Beach, B. (1975). "Expert judgment about uncertainty: Bayesian decision making in realistic settings." Organ Behav Hum Perform 14(1): 1059 Bearfield, G. and W. Marsh (2005). Generalising Event Trees Using Bayesian Networks with a Case Study of Train Derailment. in Proceedings of the 24th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2005, SpringerVerlag, vol. 3688 Beghin, I., A. De Muynck, et al. (1989). "Can the causal model approach contribute to the study of the epidemiology and the control of sleeping sickness?" Ann Soc Belg Med Trop 69 Suppl 1: 3147; discussion 144 Bellamy, S. L., J. Y. Lin, et al. (2007). "An introduction to causal modeling in clinical trials." Clin Trials 4(1): 5873 Ben Salem, A., A. Muller, et al. (2006). "Dynamic Bayesian Networks in system reliability analysis in 6th IFAC Symposium on Fault Detection, Supervision and Safety of technical processes." 6th IFAC Symposium on Fault Detection, Supervision and Safety of technical processes, China [hal00092032  version 1] (20060908" Bernardo, J. A. and A. F. Smith (1994). Bayesian Theory, John Wiley and Sons, New York. Bibi, S. and I. Stamelos (2004). Software Process Modeling with Bayesian Belief Networks. 10th International Software Metrics Symposium (Metrics 2004). Chicago, USA Biedermann, A., F. Taroni, et al. (2005). "The evaluation of evidence in the forensic investigation of fire incidents. Part II. Practical examples of the use of Bayesian networks." Forensic Science International 147(1): 5969 Birckmayer, J. D., H. D. Holder, et al. (2004). "A general causal model to guide alcohol, tobacco, and illicit drug prevention: assessing the research evidence." J Drug Educ 34(2): 12153 Blackburn, J. D., G. D. Scudder, et al. (1996). Improving speed and productivity of software development: a global survey of software developers. IEEE Transactions on Software Engineering, 22(12), 875885 Blanco, R., I. Inza, et al. (2005). "Feature selection in Bayesian classifiers for the prognosis of survival of cirrhotic patients treated with TIPS." J Biomed Inform 38(5): 37688 Bobbio, A., L. Portinale, et al. (2001). "Improving the analysis of dependable systems by mapping fault trees into Bayesian networks." Reliability Engineering and System Safety 71(3): 249260 Bockhorst, J., M. Craven, et al. (2003). "A Bayesian network approach to operon prediction." Bioinformatics 19(10): 122735 Boer, R., S. Plevritis, et al. (2004). "Diversity of model approaches for breast cancer screening: a review of model assumptions by the Cancer Intervention and Surveillance Network (CISNET) Breast Cancer Groups." Stat Methods Med Res 13(6): 52538 Borsuk, M. E., C. A. Stow, et al. (2004). "A Bayesian network of eutrophication models for synthesis, prediction, and uncertainty analysis." Ecological Modelling 173(23): 21939 Bothtner, U., S. E. Milne, et al. (2002). "Bayesian probabilistic network modeling of remifentanil and propofol interaction on wakeup time after closedloop controlled anesthesia." J Clin Monit Comput 17(1): 316 Bottcher, P., R. Stoddard, et al. (1995). A Bayesian approach for modeling quality in software products and processes. Proc 5th Int Conf Software Quality, 214253 Bouckaert, R. R. (1996). A Stratified Simulation Scheme for Inference in Bayesian Belief Networks. Utrecht University, Department of Computer Science, P.O.Box 80.089 3508 TB Utrecht, The Netherlands, email: remco@cs.ruu.nl Boudali, H. and J. B. Dugan (2005). "A discretetime Bayesian network reliability modeling and analysis framework." Reliability Engineering and System Safety 87(3): 337349 Boudali, H. and J. B. Dugan (2006). "A ContinuousTime Bayesian Network Reliability Modeling and Analysis framework." IEEE Transactions on Reliability 55: 8697 Bouissou, M., F. Martin, et al. (1999). "Assessment of a SafetyCritical System Including Software: A Bayesian Belief Network for Evidence Sources." "Free. Ann. Reliability and Maintainability Symp., RAMS" Boutilier, C., N. Friedman, et al. (1996). "Contextspecific independence in Bayesian networks." "In Proc. 12th UAI, pages 115123" Bradford, J., C. Needham, et al. (2006). "Insights into proteinprotein interfaces using a Bayesian network prediction method." J Mol Biol 362(2): 36586 Brage, D. and W. Meredith (1994). "A causal model of adolescent depression." J Psychol 128(4): 45568 Brewer, M. J. (2003). "Discretisation for inference on Bayesian mixture models." "Statistics and Computing 13, 209219" Brown, L. E., I. Tsamardinos, et al. (2004). "A novel algorithm for scalable and accurate Bayesian network learning." Medinfo 11(Pt 1): 7115 Bryan, B. and M. Garrod (2006). Combining rapid field assessment with a Bayesian network to prioritise investment in watercourse protection, CSIRO Land and Water Science Report 10/06, April, www.clw.csiro.au/publications/science/2006/sr1006.pd Bulashevska, S., O. Szakacs, et al. (2004). "Pathways of urothelial cancer progression suggested by Bayesian network analysis of allelotyping data." Int J Cancer 110(6): 8506 Burden, F. R. and D. A. Winkler (2005). "Predictive Bayesian neural network models of MHC class II peptide binding." J Mol Graph Model 23(6): 4819 Burge, J., T. Lane, et al. (2007). "Discrete dynamic Bayesian network analysis of fMRI data." Hum Brain Mapp Burnside, E., D. Rubin, et al. (2006). "Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: initial experience." Radiology 240(3): 66673 Burnside, E., D. Rubin, et al. (2000). "A Bayesian network for mammography." Proc AMIA Symp: 10610 Burnside, E., D. Rubin, et al. (2004). "Using a Bayesian network to predict the probability and type of breast cancer represented by microcalcifications on mammography." Medinfo 11(Pt 1): 137 Burnside, E. S. (2005). "Bayesian networks: computerassisted diagnosis support in radiology." Acad Radiol 12(4): 42230 Burnside, E. S., D. L. Rubin, et al. (2006). "Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: initial experience." Radiology 240(3): 66673 Burnside, E. S., D. L. Rubin, et al. (2004). "Using a Bayesian network to predict the probability and type of breast cancer represented by microcalcifications on mammography." Medinfo 11(Pt 1): 137
