计算机科学
补语(音乐)
质量(理念)
集合(抽象数据类型)
数据挖掘
选择(遗传算法)
转化(遗传学)
采样(信号处理)
结果(博弈论)
灵敏度(控制系统)
可靠性工程
机器学习
数学
工程类
表型
哲学
认识论
数理经济学
滤波器(信号处理)
基因
化学
互补
程序设计语言
生物化学
计算机视觉
电子工程
标识
DOI:10.1080/00365519950185238
摘要
General specifications of analytical goals for biochemical monitoring have been proposed based on biological within-subject variation. As a complement to this strategy for general global quality requirements there is also a need for other methods and approaches to set more optimal requirements in specific monitoring situations, i.e. application of systems and sensitivity analysis using (i) rules for propagation of errors (uncertainty) in simple algebraic/statistical transformations of laboratory results; (ii) biochemical/pathophysiological simulation models; and (iii) formalized descriptions of clinical classification and decision support processes. The possible gain in medical outcome by improving analytical and preanalytical quality should then be related to the often more important aspects of selection and combination of "tests", period and frequency of sampling/measurement, and the use of correct conceptual and computational models for transformation of data.
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