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Volumn 30, Issue 3, 2004, Pages 201-214

Bayesian networks in biomedicine and health-care

Author keywords

[No Author keywords available]

Indexed keywords

BAYES THEOREM; BIOINFORMATICS; BIOMEDICINE; DIAGNOSTIC ACCURACY; DISEASE ACTIVITY; EDITORIAL; HEALTH CARE; LEARNING; MATHEMATICAL ANALYSIS; PATIENT CARE; PRIORITY JOURNAL; PROBABILITY; PROBLEM SOLVING; PROGNOSIS; STATISTICAL CONCEPTS; STATISTICAL MODEL; TREATMENT PLANNING;

EID: 1842765480     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2003.11.001     Document Type: Editorial
Times cited : (253)

References (38)
  • 1
    • 0026868903 scopus 로고
    • Planning of therapy and tests in causal probabilistic networks
    • Andreassen S., Planning of therapy and tests in causal probabilistic networks. Artif. Intell. Med. 4:1992;227-241.
    • (1992) Artif. Intell. Med. , vol.4 , pp. 227-241
    • Andreassen, S.1
  • 5
    • 0042614837 scopus 로고    scopus 로고
    • Comparing Bayesian network classifiers
    • San Francisco, CA: Morgan Kaufmann
    • Cheng J, Greiner R. Comparing Bayesian network classifiers. In: Proceedings of the UAI'99. San Francisco, CA: Morgan Kaufmann, 1999. p. 101-7.
    • (1999) Proceedings of the uai'99 , pp. 101-107
    • Cheng, J.1    Greiner, R.2
  • 6
    • 34249832377 scopus 로고
    • A Bayesian method for the induction of probabilistic networks from data
    • Cooper G.F., Herskovitz E., A Bayesian method for the induction of probabilistic networks from data. Mach. Learn. 9:1992;309-347.
    • (1992) Mach. Learn. , vol.9 , pp. 309-347
    • Cooper, G.F.1    Herskovitz, E.2
  • 7
    • 0034262312 scopus 로고    scopus 로고
    • Sensitivity analysis: An aid for probability elicitation
    • Coupé V.M.H., van der Gaag L.C., Sensitivity analysis: an aid for probability elicitation. Knowl. Eng. Rev. 15:2000;215-232.
    • (2000) Knowl. Eng. Rev. , vol.15 , pp. 215-232
    • Coupé, V.M.H.1    Van Der Gaag, L.C.2
  • 9
    • 0002629270 scopus 로고
    • Maximisation likelihood from incomplete data via the EM algorithm
    • Dempster A., Laird N., Rubin D., Maximisation likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. B. 39:1977;1-38.
    • (1977) J. R. Stat. Soc. B , vol.39 , pp. 1-38
    • Dempster, A.1    Laird, N.2    Rubin, D.3
  • 10
    • 35248848492 scopus 로고    scopus 로고
    • Building a GA from design principles for learning Bayesian networks
    • Cantú-Paz E, Foster JA, Deb K, et al., editors. San Francisco, CA: Morgan Kaufmann
    • Van Dijk S, Thierens D, van der Gaag LC. Building a GA from design principles for learning Bayesian networks. In: Cantú-Paz E, Foster JA, Deb K, et al., editors. Proceedings of the Genetic and Evolutionary Computation Conference. San Francisco, CA: Morgan Kaufmann, 2003. p. 886-97.
    • (2003) Proceedings of the Genetic and Evolutionary Computation Conference , pp. 886-897
    • Van Dijk, S.1    Thierens, D.2    Van Der Gaag, L.C.3
  • 11
    • 0031269184 scopus 로고    scopus 로고
    • On the optimality of the simple Bayesian classifier under zero-one loss
    • Domingos P., Pazzani M., On the optimality of the simple Bayesian classifier under zero-one loss. Mach. Learn. 29:1997;103-130.
    • (1997) Mach. Learn. , vol.29 , pp. 103-130
    • Domingos, P.1    Pazzani, M.2
  • 12
    • 0031276011 scopus 로고    scopus 로고
    • On the optimality of the simple Bayesian network classifier
    • Friedman N.I.R., Geiger D., Pazzani M., On the optimality of the simple Bayesian network classifier. Mach. Learn. 29:1997;131-163.
    • (1997) Mach. Learn. , vol.29 , pp. 131-163
    • Friedman, N.I.R.1    Geiger, D.2    Pazzani, M.3
  • 14
    • 34250360429 scopus 로고    scopus 로고
    • Experiences with modelling issues in building probabilistic networks
    • Gómez-Pérez A, Benjamins VR, editors. Lecture Notes in Artificial Intelligence (LNAI) 2473. Berlin: Springer-Verlag
    • van der Gaag LC, Helsper EM. Experiences with modelling issues in building probabilistic networks. In: Gómez-Pérez A, Benjamins VR, editors. Proceedings of EKAW on Knowledge Engineering and Knowledge Management: Ontologies and the Semantic Web. Lecture Notes in Artificial Intelligence (LNAI) 2473. Berlin: Springer-Verlag, 2002. p. 21-6.
    • (2002) Proceedings of EKAW on Knowledge Engineering and Knowledge Management: Ontologies and the Semantic Web , pp. 21-26
    • Van Der Gaag, L.C.1    Helsper, E.M.2
  • 21
  • 22
    • 0026751637 scopus 로고
    • Towards normative expert systems. II. Probability-based representations for efficient knowledge acquisition and inference
    • Heckerman D.E., Nathwani B.N., Towards normative expert systems. II. Probability-based representations for efficient knowledge acquisition and inference. Meth. Inform. Med. 31:1992;106-116.
    • (1992) Meth. Inform. Med. , vol.31 , pp. 106-116
    • Heckerman, D.E.1    Nathwani, B.N.2
  • 23
    • 1842792772 scopus 로고    scopus 로고
    • Building Bayesian networks through ontologies
    • van Harmelen F, editor. Amsterdam: IOI Press
    • Helsper EM, van der Gaag LC. Building Bayesian networks through ontologies. In: van Harmelen F, editor. Proceedings of ECAI2002. Amsterdam: IOI Press, 2002. p. 680-4.
    • (2002) Proceedings of ECAI2002 , pp. 680-684
    • Helsper, E.M.1    Van Der Gaag, L.C.2
  • 24
    • 84907105901 scopus 로고
    • Converting a rule-based expert system into a belief network
    • Korver M., Lucas P.J.F., Converting a rule-based expert system into a belief network. Med. Inform. 18(3):1993;219-241.
    • (1993) Med. Inform. , vol.18 , Issue.3 , pp. 219-241
    • Korver, M.1    Lucas, P.J.F.2
  • 25
    • 0028482006 scopus 로고
    • Learning Bayesian belief networks: An approach based on the MDL principle
    • Lam W., Bacchus F., Learning Bayesian belief networks: an approach based on the MDL principle. Comput. Intell. 10:1994;269-293.
    • (1994) Comput. Intell. , vol.10 , pp. 269-293
    • Lam, W.1    Bacchus, F.2
  • 26
    • 0030245966 scopus 로고    scopus 로고
    • Structure learning of Bayesian networks by genetic algorithms: A performance analysis of control parameters
    • Larrañaga P., Poza M., Yurramendi Y., Murga R., Kuijpers C., Structure learning of Bayesian networks by genetic algorithms: a performance analysis of control parameters. IEEE Trans. Pattern Anal. Mach. Intell. 18(9):1996;912-926.
    • (1996) IEEE Trans. Pattern Anal. Mach. Intell. , vol.18 , Issue.9 , pp. 912-926
    • Larrañaga, P.1    Poza, M.2    Yurramendi, Y.3    Murga, R.4    Kuijpers, C.5
  • 27
    • 84950442428 scopus 로고
    • Propagation of probabilities, means and variances in mixed graphical models
    • Lauritzen S.L., Propagation of probabilities, means and variances in mixed graphical models. J. Am. Stat. Assoc. 87:1992;1098-1108.
    • (1992) J. Am. Stat. Assoc. , vol.87 , pp. 1098-1108
    • Lauritzen, S.L.1
  • 28
    • 0001006209 scopus 로고
    • Local computations with probabilities on graphical structures and their application to expert systems
    • Lauritzen S.L., Spiegelhalter D.J., Local computations with probabilities on graphical structures and their application to expert systems. J. R. Stat. Soc. B. 50:1987;157-224.
    • (1987) J. R. Stat. Soc. B , vol.50 , pp. 157-224
    • Lauritzen, S.L.1    Spiegelhalter, D.J.2
  • 29
    • 0342913618 scopus 로고    scopus 로고
    • Knowledge acquisition for decision-theoretic expert systems
    • Lucas P.J.F., Knowledge acquisition for decision-theoretic expert systems. AISB Q. 94:1996;23-33.
    • (1996) AISB Q. , vol.94 , pp. 23-33
    • Lucas, P.J.F.1
  • 31
    • 0031660017 scopus 로고    scopus 로고
    • Computer-based decision-support in the management of primary gastric non-Hodgkin lymphoma
    • Lucas P.J.F., Boot H., Taal B.G., Computer-based decision-support in the management of primary gastric non-Hodgkin lymphoma. Meth. Inform. Med. 37:1998;206-219.
    • (1998) Meth. Inform. Med. , vol.37 , pp. 206-219
    • Lucas, P.J.F.1    Boot, H.2    Taal, B.G.3
  • 32
    • 0034235303 scopus 로고    scopus 로고
    • A probabilistic and decision-theoretic approach to the management of infectious disease at the ICU
    • Lucas P.J.F., De Bruijn N.C., Schurink K., Hoepelman I.M., A probabilistic and decision-theoretic approach to the management of infectious disease at the ICU. Artif. Intell. Med. 19(3):2000;251-279.
    • (2000) Artif. Intell. Med. , vol.19 , Issue.3 , pp. 251-279
    • Lucas, P.J.F.1    De Bruijn, N.C.2    Schurink, K.3    Hoepelman, I.M.4
  • 35
    • 0037871273 scopus 로고    scopus 로고
    • Probability elicitation for belief networks: Issues to consider
    • Renooij S., Probability elicitation for belief networks: issues to consider. Knowl. Eng. Rev. 16(3):2001;255-269.
    • (2001) Knowl. Eng. Rev. , vol.16 , Issue.3 , pp. 255-269
    • Renooij, S.1
  • 37
    • 0022818911 scopus 로고
    • Evaluating influence diagrams
    • Shachter R.D., Evaluating influence diagrams. Oper. Res. 34(6):1986;871-882.
    • (1986) Oper. Res. , vol.34 , Issue.6 , pp. 871-882
    • Shachter, R.D.1
  • 38
    • 1842792773 scopus 로고    scopus 로고
    • A hybrid data mining approach to discover Bayesian networks using evolutionary programming
    • Langdon WB, et al., editors San Francisco, CA: Morgan Kaufmann
    • Wong ML, Lee SY, Leung KS. A hybrid data mining approach to discover Bayesian networks using evolutionary programming. In: Langdon WB, et al., editors. Proceedings of the Genetic and Evolutionary Computation Conference. San Francisco, CA: Morgan Kaufmann, 2002. p. 214-22.
    • (2002) Proceedings of the Genetic and Evolutionary Computation Conference , pp. 214-222
    • Wong, M.L.1    Lee, S.Y.2    Leung, K.S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.