Kamae I R, Greenes R A
Department of Biostatistics, Harvard School of Public Health, Brigham and Women's Hospital.
Proc Annu Symp Comput Appl Med Care. 1991:691-5.
The lack of rationale or explanation is a major deficiency of clinical algorithms. To address this issue, the authors present a computational model for associating decision analyses with clinical algorithms. Automata theory is used to model categorical reasoning with approximate Bayesian inference based on probability intervals. This approximation reduces the number of computations to linear-order instead of the exponential-order combinations of clinical findings in exact Bayes. The linkage of decision analyses and clinical algorithms by means of this model exploits a new concept of "regular" clinical algorithms and their equivalency in theory and provides valuable perspectives in practice for developers of clinical algorithms.
缺乏基本原理或解释是临床算法的一个主要缺陷。为了解决这个问题，作者提出了一种将决策分析与临床算法相关联的计算模型。自动机理论被用于基于概率区间的近似贝叶斯推理对分类推理进行建模。这种近似将计算数量减少到线性阶，而不是精确贝叶斯中临床发现的指数阶组合。通过该模型将决策分析与临床算法相联系，利用了“规则”临床算法的新概念及其理论上的等效性，并为临床算法开发者提供了有价值的实践视角。
