基于肺炎严重程度指数(PSI)值诊断肺炎的应用

E. Wahyuni, Ahmad Ramadhan
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引用次数: 3

摘要

已经进行了大量研究,根据患者的症状来诊断肺炎,有些研究使用人工智能方法,如单调法和非单调法,结果不一,根据以前的研究来开发和改进以前的研究缺陷,因为它们参考的结果预计对专家,特别是印度尼西亚的肺病专家有用。印尼肺病专科医生使用的参考指标是肺炎严重程度指数(PSI)的值,用于对肺炎程度进行分类,那么预期结果是定性和明确的输出,因此模糊逻辑Sugeno方法非常适合克服这一问题。模糊逻辑Sugeno已成功应用于肺炎疾病,并在4个数据的基础上与肺炎严重程度指数评分匹配75%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application for the diagnosis of pneumonia based on Pneumonia Severity Index (PSI) values
There has been considerable research that addresses the diagnosis of pneumonia based on symptoms experienced by the patient, some using artificial intelligent methods such as monoton and non monoton methods with mixed results, based on previous studies to develop and improve previous research deficiencies because they refer to the results is expected to be useful by experts, especially lung specialists in Indonesia, The reference used by Indonesian pulmonary specialist is the value of Pneumonia Severity Index (PSI) which is used to classify Pneumonia level, then the expected results are qualitative and unambiguous outputs therefore fuzzy logic Sugeno method is very suitable to overcome the problem. Fuzzy logic Sugeno has been successfully applied in pneumonia disease and matched with the Pneumonia Severity Index Score in the amount of 75% based on 4 data has been tested.
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