P.J.F. Lucas, H. Boot and B.G. Taal. Decision-theoretic network approach to treatment management and prognosis. Knowledge-based Systems 1998b; 11: 321--330.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....probabilistic networks [23,15,31] also known as Bayesian (belief) networks [37] and decision theory [41] that is aimed at supporting clinicians in prescribing antibiotic therapy to mechanically ventilated patients with pneumonia at the ICU. It is part of a decision theoretic expert system [25,27] called PTA (Pneumonia Therapy Advisor) Note that this problem domain is closely related to that of the well known MYCIN system, an expert system developed in the late 1970s at Stanford University that offered advice on the diagnosis and treatment of sepsis and meningitis [9,40,46] However, the ....

Lucas PJF, Boot H, Taal BG. A decision-theoretic network approach to treatment management and prognosis. Knowl Based Syst 1998;11:321 -- 30.

....probabilistic networks [23, 15, 31] also known as Bayesian (belief) networks [37] and decision theory [41] that is aimed at supporting clinicians in prescribing antibiotic therapy to mechanically ventilated patients with pneumonia at the ICU. It is part of a decision theoretic expert system [25, 27] called PTA (Pneumonia Therapy Advisor) Note that this problem domain is closely related to that of the well known mycin system, an expert system developed in the late 1970s at Stanford University that o ered advice on the diagnosis and treatment of sepsis and meningitis [9, 40, 46] However, ....

Lucas PJF, Boot H, Taal BG. A decision-theoretic network approach to treatment management and prognosis. Knowledge-based Systems 1998; 11: 321-330.

.... networks by the principal investigator, will be extended [15, 17, 34, 28, 31] When used to predict the likelihood of future events, we call these models prognostic [6, 44] Within the research team there is significant experience in building Bayesian networks for the medical domain (e.g. [36, 42, 41, 51, 2, 4]) Experience built up in the ICEA project (see Section 6.6) is particularly useful in dealing with the problem domain of infectious disease management in the ICU. 6.4.3 Learning temporal Bayesian models Learning a Bayesian network can be separated into two tasks, structure learning, ....

....its functions. The timebayes project contributes to this integral solution point of view. 6.6 Related Research and Collaboration Both Dr Peter Lucas and Prof. Linda van der Gaag have experience in building Bayesian network based systems for clinical problems in collaboration with clinicians [2, 29, 41, 4]. Dr Peter Lucas, formerly at the University of Aberdeen, has recently joined the Information Systems group at the University of Nijmegen, which is lead by Prof.dr Th.P. van der Weide, and will bring in expertise in medical informatics, medical AI (logical reasoning in medicine) Bayesian networks ....

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P.J.F. Lucas, H. Boot and B.G. Taal. Decision-theoretic network approach to treatment management and prognosis. Knowledge-based Systems 1998b; 11: 321--330.

.... by radiotherapy) Note that this declarative model of gastric NHL can be deployed for di erent tasks, such as the prediction of prognosis, treatment selection possibly using utility information yielding a decision network or in uence diagram [19, 9] and the generation of patient pro les [14]. For example, the model can be used to predict the early result and likelihood of 5 year survival after treatment by supplying patient information concerning age, general health status, clinical stage and histological features of the tumour, whether or not bulky disease (a tumour with maximum ....

P.J.F. Lucas, H. Boot and B.G. Taal. A decision-theoretic network approach to treatment management and prognosis. Knowledge-based Systems 11 (1998) 321-330.

....[7] Since the beginning of the 1990s researchers are exploring its possibilities for developing medical applications. The BN formalism offers a natural way to represent the uncertainties involved in medicine when dealing with diagnosis, treatment selection, planning, and prediction of prognosis [3]. This is due to the fact that the influences and probabilistic interactions among variables can be described readily in a BN. As the formalism is declarative in nature, any (often conditional) probabilistic statement can be computed from a given BN, where the statement may concern both individual ....

P.J.F. Lucas, H. Boot and B.G. Taal. Decision-theoretic network approach to treatment management and prognosis. Knowledge-based Systems 11 (1998) 321--330.

....As a consequence there appears to be a mismatch between common task speci c computer based models and the complexity of the eld of medicine. Bayesian networks have the virtue of being declarative models; these models can be used to explore di erent problems, and can be reused for di erent tasks [7]. They can also be employed to look at particular problems from di erent angles, just by varying the supplied evidence and the questions posed to the model. On the other hand, developing such models is challenging, both in terms of the required number of variables and the amount of probabilistic ....

P.J.F. Lucas, H. Boot and B.G. Taal. A decision-theoretic network approach to treatment management and prognosis. Knowledge-based Systems 1998; 11: 321-330.

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P.J.F. Lucas, H. Boot and B. Taal, \A decisiontheoretic network approach to treatment management and prognosis", In: A. Macintosh and R. Milne (eds.), Applications and Innovations in Expert Systems V, SGES, Cambridge, 1997, pp. 17-30.

....In this way the probabilistic information and also probabilistic computations are localised . In Figure 5, for example, Cancer is conditionally independent of Heart Disease , given the value of its immediate parent node ( Smoking ) BBNs are increasingly used in clinical and medical research [3, 16] and several probabilistic inference algorithms are available to process evidence, by manipulating the probabilities incorporated in a BBN [13, 19] It is also possible to explicitly distinguish between arcs having a temporal meaning, expressing a transition in time, and atemporal arcs, expressing ....

P.J.F. Lucas, H. Boot and B. Taal, A decision-theoretic network approach to treatment management and prognosis, in: A. Macintosh and R. Milne, eds., Applications and Innovations in Expert Systems V (SGES, Cambridge, 1997) 17-30.

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