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不同的策略旨在运用在临床推理决策——演绎或诊断推理(2 9 10),决策分析,(2、3、9),模式识别[9][9 – 11]和直觉。在——演绎推理假设生成基于病人的数据,然后进行测试,进一步假设生成假设证实或反驳。用来解决陌生问题或一个复杂的表达[10]。决策分析提供病人偏好作为输入对临床决策[2,3]。冯·诺依曼和Morgenstern首次提出,价值观和态度驱动个人推理选择可以通过数学公式理解[3]。后来,莱德利,贪念使用决策分析来展示数学学科——数理逻辑与概率的概念有助于我们理解医学诊断的推理基础[1,3]。模式识别是一种归纳推理,当前病人的问题与之前见过的相关临床问题和采用以前成功的治疗,专家和经验丰富的从业人员,往往是更快和更高效的[10]。直觉是不被认为是一种科学知识在临床推理[9]。启发式和经验知识使用有效地处理大量的信息汤普森,维亚道丁。2002)是重要的但不是充分依据医疗决策,往往在决策中引入一系列的偏见。[12]。


Different strategies aimed at decision making use in clinical reasoning are Hypothetico-deductive or diagnostic reasoning [2, 9, 10], Decision analysis, [2, 3, 9], Pattern recognition [9-11] and Intuition [9]. In hypothetico-deductive reasoning hypothesis is generated based on data from the patient, which is then tested, and further hypotheses are generated to confirm or refute the hypotheses. Use to solve unfamiliar problem or a complex presentation [10]. Decision analysis make patient preferences available as input for clinical decision- making [2, 3]. Von Neumann and Morgenstern first proposed that values and attitudes that drive individual reasoning choice could be understood through mathematical formulations [3]. Later, Ledley & Lusted use decision analysis to show how the concepts of mathematical disciplines – symbolic logic and probability can contribute to our understanding of the reasoning foundations of medical diagnosis [1, 3]. Pattern recognition is an inductive reasoning, the current patient’s problems are associated with previously-seen clinical problems and a previously-successful treatment is adopted, used by expert and experienced practitioners, tends to be faster and more efficient [10]. Intuition is not recognized as a source of scientific knowledge in clinical reasoning [9].Heuristics and experiential knowledge use to process large amount of information efficiently Thompson & Dowding. 2002) are important but not a sufficient basis for medical decision making, tend to introduce series of biases into decisions making. [12].


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