Jahantigh Farzad Firouzi, Malmir Behnam, Avilaq Behzad Aslani
Department of Industrial Engineering, University of Sistan and Baluchestan, Zahedan, Iran.
Department of Industrial and Manufacturing Systems Engineering, Kansas State University, Manhattan, KS, USA.
Kidney Res Clin Pract. 2017 Mar;36(1):29-38. doi: 10.23876/j.krcp.2017.36.1.29. Epub 2017 Mar 31.
Disease diagnosis is complicated since patients may demonstrate similar symptoms but physician may diagnose different diseases. There are a few number of investigations aimed to create a fuzzy expert system, as a computer aided system for disease diagnosis.
In this research, a cross-sectional descriptive study conducted in a kidney clinic in Tehran, Iran in 2012. Medical diagnosis fuzzy rules applied, and a set of symptoms related to the set of considered diseases defined. The input case to be diagnosed defined by assigning a fuzzy value to each symptom and then three physicians asked about each suspected diseases. Then comments of those three physicians summarized for each disease. The fuzzy inference applied to obtain a decision fuzzy set for each disease, and crisp decision values attained to determine the certainty of existence for each disease.
Results indicated that, in the diagnosis of seven cases of kidney disease by examining 21 indicators using fuzzy expert system, kidney stone disease with 63% certainty was the most probable, renal tubular was at the lowest level with 15%, and other kidney diseases were at the other levels. The most remarkable finding of this study was that results of kidney disease diagnosis (e.g., kidney stone) via fuzzy expert system were fully compatible with those of kidney physicians.
The proposed fuzzy expert system is a valid, reliable, and flexible instrument to diagnose several typical input cases. The developed system decreases the effort of initial physical checking and manual feeding of input symptoms.
疾病诊断很复杂，因为患者可能表现出相似的症状，但医生可能诊断出不同的疾病。有一些研究旨在创建一个模糊专家系统，作为一种用于疾病诊断的计算机辅助系统。
本研究于2012年在伊朗德黑兰的一家肾脏诊所进行了一项横断面描述性研究。应用医学诊断模糊规则，并定义了一组与所考虑疾病相关的症状。通过为每个症状赋予一个模糊值来定义要诊断的输入病例，然后询问三位医生关于每种疑似疾病的情况。然后总结这三位医生对每种疾病的评论。应用模糊推理来获得每种疾病的决策模糊集，并获得清晰的决策值以确定每种疾病存在的确定性。
结果表明，在使用模糊专家系统通过检查21项指标对7例肾脏疾病进行诊断时，肾结石疾病的确诊可能性最高，为63%，肾小管疾病的确诊可能性最低，为15%，其他肾脏疾病处于其他水平。本研究最显著的发现是，通过模糊专家系统进行的肾脏疾病诊断（如肾结石）结果与肾脏科医生的诊断结果完全一致。
所提出的模糊专家系统是一种有效、可靠且灵活的工具，可用于诊断几种典型的输入病例。所开发的系统减少了初始身体检查的工作量和输入症状的手动输入。
