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用于中风患者诊断和治疗的单病例模糊逻辑与因果推理。

Fuzzy logic and causal reasoning with an 'n' of 1 for diagnosis and treatment of the stroke patient.

作者信息

Helgason Cathy M, Jobe Thomas H

机构信息

Department of Neurology, University of Illinois College of Medicine in Chicago, 912 South Wood Street, Room 855 N, Chicago, IL 60612, USA.

出版信息

Expert Rev Neurother. 2004 Mar;4(2):249-54. doi: 10.1586/14737175.4.2.249.

Abstract

The current scientific model for clinical decision-making is founded on binary or Aristotelian logic, classical set theory and probability-based statistics. Evidence-based medicine has been established as the basis for clinical recommendations. There is a problem with this scientific model when the physician must diagnose and treat the individual patient. The problem is a paradox, which is that the scientific model of evidence-based medicine is based upon a hypothesis aimed at the group and therefore, any conclusions cannot be extrapolated but to a degree to the individual patient. This extrapolation is dependent upon the expertise of the physician. A fuzzy logic multivalued-based scientific model allows this expertise to be numerically represented and solves the clinical paradox of evidence-based medicine.

摘要

当前临床决策的科学模型基于二元逻辑或亚里士多德逻辑、经典集合论以及基于概率的统计学。循证医学已被确立为临床建议的基础。当医生必须对个体患者进行诊断和治疗时,这种科学模型存在一个问题。这个问题是一个悖论,即循证医学的科学模型基于针对群体的假设,因此,任何结论都不能直接外推至个体患者,只能在一定程度上进行外推。这种外推依赖于医生的专业知识。基于模糊逻辑多值的科学模型允许将这种专业知识以数字形式表示,并解决了循证医学的临床悖论。

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