Decision analysis as the basis for computer-aided management of acute renal failure

Gorry, G. Anthony; Kassirer, Jerome P.; Essig, Alvin; Schwartz, William B.

doi:10.1016/0002-9343(73)90204-0

Cited by 137 publications

(37 citation statements)

References 3 publications

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“…He used the acute renal failure program discussed in Section 7.2 ( 33] as an example of the problems arising when decision analysis is used alone . In particular , he analyzed some of the cases on which the program had failed but the physicians considering the cases had performed well.…”

Section: Overviewmentioning

confidence: 99%

Knowledge engineering for medical decision making: A review of computer-based clinical decision aids

1979

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Section: Overviewmentioning

confidence: 99%

Knowledge engineering for medical decision making: A review of computer-based clinical decision aids

1979

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“…Similarly, the test-selection strategy used in sequential diagnosis is likely to affect the number of tests required, on average, to reach a solution. Another issue to be addressed by further research is how evidential power compares with alternative measures such as entropy [2] in terms of average dialogue length before any reduction based on look-ahead search.…”

Section: Related Workmentioning

confidence: 99%

“…In sequential diagnosis, tests are selected on the basis of their ability to discriminate between competing hypotheses that may account for an observed symptom or fault [1][2][3][4]. In spite of the strong assumptions on which it is based, the independence Bayesian approach to diagnosis (also known as Naïve Bayes) often works well in practice, for example in domains such as the diagnosis of acute abdominal pain [5,6].…”

Section: Introductionmentioning

confidence: 99%

“…In spite of the strong assumptions on which it is based, the independence Bayesian approach to diagnosis (also known as Naïve Bayes) often works well in practice, for example in domains such as the diagnosis of acute abdominal pain [5,6]. Early approaches to test selection in the independence Bayesian framework were based on the method of minimum entropy, in which priority is given to the test that minimises the expected entropy of the distribution of posterior probabilities [2]. A similar strategy is the basis of the theory of measurements developed by deKleer and Williams, who combined model-based reasoning with sequential diagnosis in a system for localising faults in digital circuits [1].…”

Section: Introductionmentioning

confidence: 99%

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Sequential diagnosis in the independence Bayesian framework

McSherry¹

2003

Soft Computing - A Fusion of Foundations, Methodologies and App

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We present a new approach to test selection in sequential diagnosis (or classification) in the independence Bayesian framework that resembles the hypotheticodeductive approach to test selection used by doctors. In spite of its relative simplicity in comparison with previous models of hypothetico-deductive reasoning, the approach retains the advantage that the relevance of a selected test can be explained in strategic terms. We also examine possible approaches to the problem of deciding when there is sufficient evidence to discontinue testing, and thus avoid the risks and costs associated with unnecessary tests.

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“…Clinical decision analysis has been well-studied and is known for its ability to handle the tradeoffs 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].…”

Section: Introductionmentioning

confidence: 99%

Ranking radiotherapy treatment plans using decision-analytic and heuristic techniques

Jain

Kahn

1992

Computers and Biomedical Research

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Radiotherapy treatment optimization is done by generating a set of tentative treatment plans, evaluating them and selecting the plan closest to achieving a set of conflicting treatment objectives. The evaluation of potential plans involves making tradeoffs among competing possible outcomes. Multiattribute decision theory provides a framework for specifying such tradeoffs and using them to select optimal actions. Using these concepts, we have developed a plan-ranking model which ranks a set of tentative treatment plans from best to worst. Heuristics are used to refine this model so that it reflects the clinical condition of the patient being treated and the practice preferences of the physician prescribing the treatment. A figure of merit is computed for each tentative plan, and is used to rank the plans. The approach described is very general and can be used for other medical domains having similar characteristics. The figure of merit can also be used as an objective function by computer programs that attempt to automatically generate an optimal treatment plan.

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Decision analysis as the basis for computer-aided management of acute renal failure

Cited by 137 publications

References 3 publications

Knowledge engineering for medical decision making: A review of computer-based clinical decision aids

Knowledge engineering for medical decision making: A review of computer-based clinical decision aids

Sequential diagnosis in the independence Bayesian framework

Ranking radiotherapy treatment plans using decision-analytic and heuristic techniques

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