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Yearb Med Inform 2004; 13(01): 505-507
DOI: 10.1055/s-0038-1638189
DOI: 10.1055/s-0038-1638189
Synopsis
Decision Support, Knowledge Representation and Management
Weitere Informationen
Address of the author:
György Kozmann, Ph.D., D.Sc.
Department of Information Systems
University of Veszprém
Veszprém, Hungary
eMail: kozmann@irt.vein.hu
Publikationsverlauf
Publikationsdatum:
05. März 2018 (online)
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References
- 1 Kaufman DR, Patel VL, Hilliman C, Morin PC, Pevzner J, Weinstock RS. et al. Usability in the real world: assessing medical information technologies in patients’ homes. J Biomed Inform 2003; 36 1-2 45-60.
- 2 Morrison ML, McCluggage WG, Price GJ, Diamond J, Sheeran MRM, Mulholland KM, Walsh et al. Expert system support using a Bayesian belief network for the classification of endometrial hyperplasia. J Pathol 2002; 197: 403-14.
- 3 Peleg M, Yeh I, Altman RB. Modelling biological processes using workflow and Petri Net models. Bioinformatics 2002; 18: 825-37.
- 4 Peters A, Lausen B, Michelson G, Gefeller O. Diagnosis of Glaucoma by Indirect Classifiers. Methods Inf Med 2003; 42: 99-103.
- 5 Prado M, Reina-Tosina LRJ, Palma A, Milán JA. Virtual Center for Renal Support: Technological Approach to Patient Physiological Image. IEEE Trans Biomed Eng 2002; 49: 1420-30.
- 6 Montironi R, Whimster WF, Collan Y, Hamilton PW, Thomson D, Bartels PH. How to develop and use a Bayesian Belief Network. J Clin Pathol 1996; 49 (03) 194-201.
- 7 Mardin CY, Hothorn T, Peters A, Junemann AG, Nguyen NX, Lausen B. New glaucoma classification method based on standard Heidelberg Retina Tomograph parameters by bagging classification trees. J Glaucoma 2003; 12 (04) 340-6.
Address of the author:
György Kozmann, Ph.D., D.Sc.
Department of Information Systems
University of Veszprém
Veszprém, Hungary
eMail: kozmann@irt.vein.hu
-
References
- 1 Kaufman DR, Patel VL, Hilliman C, Morin PC, Pevzner J, Weinstock RS. et al. Usability in the real world: assessing medical information technologies in patients’ homes. J Biomed Inform 2003; 36 1-2 45-60.
- 2 Morrison ML, McCluggage WG, Price GJ, Diamond J, Sheeran MRM, Mulholland KM, Walsh et al. Expert system support using a Bayesian belief network for the classification of endometrial hyperplasia. J Pathol 2002; 197: 403-14.
- 3 Peleg M, Yeh I, Altman RB. Modelling biological processes using workflow and Petri Net models. Bioinformatics 2002; 18: 825-37.
- 4 Peters A, Lausen B, Michelson G, Gefeller O. Diagnosis of Glaucoma by Indirect Classifiers. Methods Inf Med 2003; 42: 99-103.
- 5 Prado M, Reina-Tosina LRJ, Palma A, Milán JA. Virtual Center for Renal Support: Technological Approach to Patient Physiological Image. IEEE Trans Biomed Eng 2002; 49: 1420-30.
- 6 Montironi R, Whimster WF, Collan Y, Hamilton PW, Thomson D, Bartels PH. How to develop and use a Bayesian Belief Network. J Clin Pathol 1996; 49 (03) 194-201.
- 7 Mardin CY, Hothorn T, Peters A, Junemann AG, Nguyen NX, Lausen B. New glaucoma classification method based on standard Heidelberg Retina Tomograph parameters by bagging classification trees. J Glaucoma 2003; 12 (04) 340-6.