Leaper D J, Horrocks J C, Staniland J R, De Dombal F T
Br Med J. 1972 Nov 11;4(5836):350-4. doi: 10.1136/bmj.4.5836.350.
This paper reports a comparison between two modes of computer-aided diagnosis in a real-time prospective trial involving 472 patients with acute abdominal pain. In the first mode the computer-aided system analysed each of the 472 patients by referring to data previously collated from a large series of 600 real-life patients. In the second mode the system used as a basis for its analysis "estimates" of probability provided by a group of six clinicians. The accuracy and reliability of both modes were compared with the performance of unaided clinicians.Using "real-life" data the computer system was significantly more effective than the unaided clinician. By contrast, when using the clinicians' own estimates the computer-aided system was often less effective than the unaided clinician-especially when diagnosing less common disorders. It seems, firstly, that future systems for computer-aided diagnosis should employ data from real-life and not clinicians' estimates, and, secondly, that clinicians themselves cannot analyse cases in a probabilistic fashion, since often they have little idea of what the "true" probabilities are.
本文报告了在一项涉及472例急性腹痛患者的实时前瞻性试验中,对两种计算机辅助诊断模式的比较。在第一种模式中,计算机辅助系统通过参考先前从600例大量真实患者中整理的数据,对472例患者中的每一位进行分析。在第二种模式中,系统将一组六名临床医生提供的概率“估计值”作为其分析的基础。将这两种模式的准确性和可靠性与未借助辅助工具的临床医生的表现进行了比较。使用“真实”数据时,计算机系统比未借助辅助工具的临床医生显著更有效。相比之下,当使用临床医生自己的估计值时,计算机辅助系统往往不如未借助辅助工具的临床医生有效——尤其是在诊断不太常见的疾病时。首先,未来的计算机辅助诊断系统似乎应该采用来自真实病例的数据,而不是临床医生的估计值;其次,临床医生自己无法以概率方式分析病例,因为他们往往对“真实”概率几乎一无所知。