Lucas, P.J., de Bruijn, N.C., Schurink, K., and Hoepelman, A. 2000. A probabilistic and decision theoretic approach to the management of infectious disease at the ICU. Artificial Intelligence in Medicine 19(3):251-279. Home/Search Document Details and Download
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Building Probabilistic Networks: Where Do the Numbers.. - Druzdzel, van der Gaag (1995) (10 citations) (Correct)
....once it has been constructed. Also, the variables and associated values that are recorded in the data collection should match the variables and values that are to be modeled in the network, or should at least admit transformation into these variables and values without too much loss of information [Lucas et al. 2000]. The data collection should further comprise enough data to allow for reliable identification of probabilistic relationships among the variables discerned and to provide for reliable probability assessments. In an insu#ciently large data collection, the various subsets from which probabilities ....
P.J.F. Lucas, N.C. de Bruijn, K. Schurink, and I.M. Hoepelman. A probabilistic and decision-theoretic approach to the management of infectious disease at the ICU. Artificial Intelligence in Medicine, vol. 19, 2000, pp. 251 -- 279.
Parameter Estimation in Large Causal - Independence Models Rasa Self-citation (Lucas) (Correct)
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Lucas, P.J.F., Bruijn, N.C. de, Schurink, K. and Hoepelman, I.M. (2000). Probabilistic and Decision-theoretic Approach to the Management of Infectious Disease in the ICU, Artificial Intelligence in Medicine, 19, pp. 251-279.
A Probabilistic-network Model for the.. - de Bruijn.. Self-citation (Lucas De bruijn Schurink Hoepelman) (Correct)
....required by a decision support system are already, at least partially, available on line, the burden of getting clinicians to deploy decision support systems in every day practice is also rendered less large. Within three of four ICUs in the University Medical Centre Utrecht a clinical information system (C2000, sold by the Eclipsys corporation) is used to collect the data generated by the medical equipment connected to the patient, as well as for the gathering, storage and retrieval of clinical data, such as the medical history and the results of physical examination. The data are stored in a modern ....
....of major importance. When possible the expert judgments were adjusted to re ect statistical information in the literature. Figure 1 gives an overview of the structure of the model. A more complete description of the model, including a more extensive motivation of its structure, is given in Ref. 9 ] colonisation pneumonia colonisation PA colonisation HI colonisation SP pneumonia PA pneumonia HI pneumonia SP pneumonia symptoms signs lab hospitalisation aspiration mechanical ventilation immunological status susceptibility coverage medication side e ects Figure ....
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P.J.F. Lucas, N.C. de Bruijn, K. Schurink, I.M. Hoepelman, A Probabilistic and decisiontheoretic approach to the management of infectious disease at the ICU, Articial Intelligence in Medicine 19(3) (2000) 251-279.
Bayesian Networks in Medicine: a Model-based Approach to Medical.. - Lucas Self-citation (Lucas) (Correct)
....of their use in medical decision making, in particular diagnosis, prognostic) prediction and treatment selection. A BN model that was developed to assist clinicians in the diagnosis and selection of antibiotic treatment for patients with pneumonia in the ICU is taken as a running example [5]. 2 Modelling Developing a model of a realistic medical problem is usually far from easy, and using Bayesian networks yields no exception in this respect. As is the case with other representation formalisms, there are particular guidelines which facilitate developing a BN [4] We start by ....
....function to the interval 27 , and Bayesian network inference algorithms can be used to determine (the sequence of) optimal decisions. In the VAP model, this mapping is very straightforward, as there is only one decision to make (antibiotic therapy) The actual mapping is derived in Ref. [5]. 4 Evaluation Evaluation of a Bayesian network and decision theoretic system is not much different from evaluation of any decision support system. Measures such as true positive and true negative rates can be determines, as accuracy and predictive power for a test dataset with patient data. As ....
P.J.F. Lucas, N.C. de Bruijn, K. Schurink, I.M. Hoepelman, A Probabilistic and decision-theoretic approach to the management of infectious disease at the ICU, Artificial Intelligence in Medicine 19(3) (2000) 251--279.
Speeding up Inference in Markovian Models - Theodore Charitos Peter (Correct)
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Lucas, P.J., de Bruijn, N.C., Schurink, K., and Hoepelman, A. 2000. A probabilistic and decision theoretic approach to the management of infectious disease at the ICU. Artificial Intelligence in Medicine 19(3):251-279.
Building Probabilistic Networks: Where Do the Numbers Come.. - Druzdzel, van der Gaag (2000) (10 citations) (Correct)
No context found.
P.J.F. Lucas, N.C. de Bruijn, K. Schurink, and I.M. Hoepelman. A probabilistic and decision-theoretic approach to the management of infectious disease at the ICU. Arti cial Intelligence in Medicine, vol. 19, 2000, pp. 251 - 279.
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