Simonyi J, Lehoczky J, Herpai Z, Gödry A, Szauder I
J Biomed Eng. 1980 Jul;2(3):177-84. doi: 10.1016/0141-5425(80)90144-2.
A discriminating program was developed on the basis of time, dynamic and simply calculated parameters of non-invasive tracings recorded in the supine position. Data were derived from ECG, PCG and the indirect carotid pulse curve. The optimal program, formed after 40 experimental processes, was in 85% agreement with the clinical diagnosis. To improve the decision process, we created a new 'test again' group, in addition to the healthy and sick groups. The 'test again' group included 16.5% of the examined subjects. At the same time, there was 75.6% agreement with the clinical diagnosis, and 7.9% disagreement. The risk factors, which could be demonstrated as part of the 'errors' called attention to undetected heart failure. The descriminating function found to be best, was fed into a small computer (R-10). Records for evaluation were entered on magnetic tape to the computer which measured automatically the necessary parameters and printed out the 'decision': 'healthy', 'test again!', or 'cardiac patient', as well as other data, such as systolic time intervals, etc. There is a wide potential application for automated computer system based on non-invasive parameters.
基于仰卧位记录的无创描记图的时间、动态及简单计算参数，开发了一种判别程序。数据来源于心电图、心音图和间接颈动脉搏动曲线。经过40次实验过程后形成的最佳程序与临床诊断的符合率为85%。为了改进决策过程，除了健康组和患病组外，我们创建了一个新的“再次测试”组。“再次测试”组包括16.5%的受检者。同时，与临床诊断的符合率为75.6%，不符合率为7.9%。作为“错误”一部分而被证明的危险因素引起了对未被检测到的心力衰竭的关注。发现最佳的判别功能被输入到一台小型计算机（R - 10）中。用于评估的记录被录入磁带，然后输入到计算机中，该计算机自动测量必要的参数并打印出“决策”：“健康”、“再次测试！”或“心脏病患者”，以及其他数据，如收缩期时间间期等。基于无创参数的自动化计算机系统有广泛的潜在应用。
