Bay K S, Lee S J, Flathman D P, Roll J W, Piercy W
Can Med Assoc J. 1976 Nov 6;115(9):887-92.
A retrospective study was carried out to assess the feasibility of computer-assisted prognostication by discriminant analysis and the Bayesian classification procedure based on clinical information collected on patients with acute myocardial infarction. The overall accuracy was 94.2% in predicting hospital death but the prediction of late death after discharge was less accurate. It was found that not all of the 44 variables used for analysis were necessary to reach the same level of predictive accuracy--16 to 20 variables would result in almost the identical prediction. The Bayesian classification procedure was applied to estimate probabilities of individual patients belonging to the different prognostic categories.
开展了一项回顾性研究，以评估基于急性心肌梗死患者收集的临床信息，通过判别分析和贝叶斯分类程序进行计算机辅助预后评估的可行性。预测医院死亡的总体准确率为94.2%，但出院后晚期死亡的预测准确性较低。研究发现，并非用于分析的所有44个变量对于达到相同水平的预测准确性都是必需的——16至20个变量将产生几乎相同的预测结果。应用贝叶斯分类程序来估计个体患者属于不同预后类别的概率。
