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A new scientific accuracy measure for performance evaluation of human-computer diagnostic systems

机译:一种新的人机诊断系统性能评估的新型科学准确度措施

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This paper first presents a new scientific accuracy measure (denoted by G) for assessing/evaluating the performance of computer medical diagnostic (CMD) systems by incorporating the true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN) of human and computer's diagnoses with respect to each other. Based on G, a formula for computing a multi-parameter sensitivity vector S (G), with the assumption that the system parameter percentage variations are small, is then proposed. For a given set of parameter percentage errors, from the expression of S (G), we can compute the error bound of G and assess the reliability of the system with human and/or computer errors being taken into consideration. It has been demonstrated that the new measure G is capable of providing consistent performance evaluation of a CMD system in general. Based on the value of G, a CMD system can be classified as having "good", "fair", or "poor" performance. Even though the proposed basic accuracy measure and its sensitivity study are derived based on the diagnosis using two diagnostic categories (positive and negative) compared by two observers (a human expert and a computer system), however, its methodology can be extended to CMD systems with multiple diagnostic categories and observers. The formulas for measuring the performance of such systems are discussed and present.
机译:本文首先提出了一种新的科学准确度(由G表示),用于评估/评估计算机医疗诊断(CMD)系统的性能来纳入真正的阳性(TP),真正的否定(TN),误报(FP)和人类和计算机对彼此诊断的假阴性(FN)。基于G,用于计算多参数灵敏度矢量s(g)的公式,假设系统参数百分比变化很小,则会提出。对于给定的一组参数百分比错误,从S(g)的表达式,我们可以计算G的误差并评估系统的可靠性和/或计算机错误被考虑。已经证明,新的措施G能够一般提供CMD系统的一致性评估。基于G的值,CMD系统可以被归类为“良好”,“公平”或“差”性能。尽管基于由两个观察者(人类专家和计算机系统)比较的使用两个诊断类别(正负)来得出所提出的基本准确度和其敏感性研究,但其方法可以扩展到CMD系统具有多个诊断类别和观察员。讨论和存在用于测量这种系统性能的公式。

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