Weinstein MC, Fineberg HV. Clinical decision analysis. Philadelphia, PA: W.B. Saunders, 1980:84--94.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... judgments comparing at least two attributes [13, 38] and analytic hierarchy process which requires pairwise strength of preference judgments [62] Clinical decision analysis has been well studied and has been shown to handle e#ectively the problems faced in routine medical decision making [35, 50, 68, 75]. A clinical decision support system is any computer program designed to help health professionals in making clinical decisions [67] One class of medical decision making problems addressed by clinical decision analysis is the selection of the optimal therapy plan from competing therapy plans. ....

Weinstein MC, Fineberg HV. Clinical Decision Analysis. W. B. Saunders, Philadelphia, PA, 1980.

....environments. Specifically, costs and benefits usually are not known precisely, and class distributions often are known only approximately as well. This fact has been pointed out by many authors (Bradley 1997; Catlett 1995) and is in fact the concern of a large subfield of decision analysis (Weinstein Fineberg 1980). Imprecision also arises because the environment may change between the time the system is conceived and the time it is used, and even as it is used. For example, levels of fraud and levels of customer responsiveness change continually over time and from place to place. In this paper we address ....

....show that it is also robust for a variety of other practical metrics. After that we discuss how the rocch can be used in imprecise environments. Finally, we show that for some problems the rocch hybrid can actually do better than all known classifiers. Minimizing expected cost Decision analysis (Weinstein Fineberg 1980) provides us with a method for determining when one classification model is better than another. Specifically, the expected cost of applying a classifier is: p(p) Delta (1 Gamma TP ) Delta c(N; p) p(n) Delta FP Delta c(Y; n) 1) We now can show that the rocch hybrid is robust for problems ....

Weinstein, M. C., and Fineberg, H. V. 1980. Clinical Decision Analysis. Philadelphia, PA: W. B. Saunders Company.

....Specifically, costs and benefits usually are not known precisely, and target class distributions often are known only approximately as well. This observation has been made by many authors (Bradley, 1997; Catlett, 1995) and is in fact the concern of a large subfield of decision analysis (Weinstein Fineberg, 1980). Imprecision also arises because the environment may change between the time the system is conceived and the time it is used, and even as it is used. For example, levels of fraud and levels of customer responsiveness change continually over time and from place to place. Running head: Robust ....

....even less guidance in situations where distributions are imprecise or can change. If a model produces an estimate of p(pjI) the posterior probability of an instance s class membership, as most machine learned models can, decision analysis gives us a way to produce cost sensitive classifications (Weinstein Fineberg, 1980). Classifier error frequencies can be used to approximate probabilities (Pazzani et al. 1994) For an instance I , the decision to emit a positive classification from a particular classifier is: 1 Gamma p(pjI) Delta c(Y; n) p(pjI) Delta c(N; p) Regardless of whether a classifier produces ....

Weinstein, M. C., & Fineberg, H. V. (1980). Clinical Decision Analysis. Philadelphi, PA: W. B. Saunders Company.

....environments. Specifically, costs and benefits usually are not known precisely, and class distributions often are known only approximately as well. This fact has been pointed out by many authors (Bradley 1997; Catlett 1995) and is in fact the concern of a large subfield of decision analysis (Weinstein Fineberg 1980). Imprecision also arises because the environment may change between the time the system is conceived and the time it is used, and even as it is used. For example, levels of fraud and levels of customer responsiveness change continually over time and from place to place. In this paper we address ....

....provides a deep understanding of why the rocch hybrid works. We then show that it is also robust for a variety of other practical metrics. Finally, we show that for some problems the rocch hybrid can actually do better than all known classifiers. Minimizing expected cost Decision analysis (Weinstein Fineberg 1980) provides us with a method for determining when one classification model is better than another. Specifically, 4 The convex hull in ROC space is above the line y = x, which corresponds to weighted random guessing. All proper classifiers are above the line y = x (Egan 1975) the expected cost ....

Weinstein, M. C., and Fineberg, H. V. 1980. Clinical Decision Analysis. Philadelphi, PA: W. B. Saunders Company.

....class) be a two place error cost function where c(Y; n) is the cost of a false positive error and c(N; p) is the cost of a false negative error 1 . If a classifier produces posterior probabilities, decision analysis gives us a way to produce cost sensitive classifications from the classifier (Weinstein Fineberg 1980). Classifier error frequencies can be used to approximate probabilities (Pazzani et al. 1994) For an instance I , the decision to emit a positive classification is: 1 Gamma p(pjI) Delta c(Y; n) p(pjI) Delta c(N; p) Regardless of whether a classifier produces probabilistic or binary ....

Weinstein, M. C., and Fineberg, H. V. 1980. Clinical Decision Analysis. Philadelphi, PA: W. B. Saunders Company.

....be on the three class version of the MAX domain (cleaned up data) 6.1 Evaluating Results: Cost Effectiveness and Accuracy We now consider the cost that would be incurred by any incorrect decisions made. This task is complicated by the fact that, as discussed in the decision analysis literature (Weinstein Fineberg, 1980), it is often difficult to estimate costs. For instance, certain tests in the central office might require much more time than others, resulting in higher labor costs to determine that the trouble is elsewhere. We interviewed experts to determine, as well as we can, the error costs associated with ....

....Pazzani, et al. 1994) we postulate that a cost sensitive decision stump is a relatively strong straw man for cost sensitive machine learning work. Interested researchers can begin by referencing work in statistics (Duda Hart, 1973) decision analysis (Henrion, et al. 1991; Keeney, 1982; Weinstein Fineberg, 1980), and pattern recognition (Dattatreya Kanal, 1985) Webb (1996) gives an overview of recent work on cost sensitive machine learning. Acknowledgements Tom Fawcett helped in developing new mappings from field technicians resolution codes to dispatches. Kim Tabtiang performed the runs reported in ....

Weinstein, M. C., and Fineberg, H. V. (1980). Clinical Decision Analysis. Philadelphia, PA: W.B. Saunders Company.

....is assessed and so are the probabilities of events that may occur due to a possible action. The sequence of actions which maximizes the expected utility is chosen. Clinical decision analysis has been well studied and is known for its ability to handle the tradeo#s faced by the decision maker [10, 16, 17, 18]. In particular, decision analysis has been used as a methodology for evaluating therapy plans [2] and for selecting among therapeutic options [4] For some di#cult decision problems, it is not possible to assign a single utility to the outcomes. In those cases, a multiattribute utility model is ....

MC Weinstein and HV Fineberg. Clinical Decision Analysis. W. B. Saunders Company, Philadelphia, PA, 1980.

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Weinstein MC, Fineberg HV. Clinical decision analysis. Philadelphia, PA: W.B. Saunders, 1980:84--94.

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Weinstein MF,Finenberg HV. Clinical Decision Analysis. Philadelphia, PA: WB Saunders,

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Weinstein, M. C.; Fineberg, H. V. Clinical Decision Analysis. Philadelphia, PA: W. B. Saunders; 1980.

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M. Weinstein and H. Fineberg, Clinical Decision Analysis. Philadelphia: W.B. Saunders Company, 1980.

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Weinstein M. C. & Fineberg H. V. (1980) Clinical Decision Analysis. W.B. Saunders Company, Philadelphia, PA.

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