Stern R B, Knill-Jones R P, Williams R
Br Med J. 1975 Jun 21;2(5972):659-62. doi: 10.1136/bmj.2.5972.659.
A computer-assisted model for diagnosing jaundice has been adapted for use on the University of London C.D.C. 7600 computer via an on-line terminal at King's College Hospital to provide a rapid turn-round time. The model was used prospectively in the diagnosis of 219 patients--135 seen in a specialized liver unit and 84 seen in one of four district hospitals in south-east London--with an overall accuracy in distinguishing among 11 different causes of jaundice of 69% and 62% respectively. These figures rose to 77% and 88% respectively when only those patients in whom the final diagnosis reached a "certain" probability were considered. When used to distinguish between a medical and a surgical cause of jaundice the accuracy was 86% in the liver unit and 77% in the district hospitals, rising to 95% in both series for those with a diagnosis of certain probability. The proposed improvements to the model--namely, the use of two deparate data bases and more diagnoses within the matrix--should be improve the accuracy even further. In practice the rapid feedback to the clinicians looking after patients provided help in managing difficult cases.
一种用于诊断黄疸的计算机辅助模型已通过国王学院医院的在线终端,适配到伦敦大学的CDC 7600计算机上使用,以实现快速周转时间。该模型被前瞻性地用于诊断219例患者,其中135例在专门的肝病科就诊,84例在伦敦东南部四家地区医院之一就诊。在区分11种不同黄疸病因时,总体准确率分别为69%和62%。当仅考虑最终诊断达到“确定”概率的患者时,这些数字分别升至77%和88%。当用于区分黄疸的内科和外科病因时,肝病科的准确率为86%,地区医院为77%,对于诊断为确定概率的患者,两个系列的准确率均升至95%。对该模型提出的改进措施,即使用两个独立的数据库以及矩阵内更多的诊断项目,应能进一步提高准确率。在实际应用中,快速反馈给照顾患者的临床医生,有助于处理疑难病例。