Chronic kidney disease is a life-threatening complication. Primary diagnosis and active control avoid its progression. To increase the life span of a patient, it is necessary to detect such diseases in early stages. In this research paper, design and development of a fuzzy expert system (FES) to identify the current stage of chronic kidney disease is proposed. The proposed fuzzy rule-based expert system is developed with the help of clinical practice guidelines, database, and the knowledge of a team of specialists. It makes use of input variables like nephron functionality, blood sugar, diastolic blood pressure, systolic blood pressure, age, body mass index (BMI), and smoke. The normality tests are applied on different input parameters. The input variables, i.e., nephron functionality, blood sugar, and BMI have more impact on the chronic kidney disease as shown by the response of surface analysis. The output of the system shows the current stage of patient’s kidney disease. Totally 80 tests were performed on the FES developed in this research work, and the generated output was compared with expected output. It is observed that this system succeeds in 93.75% of the tests. This system supports the doctors in assessment of chronic kidney disease among patients. The detection of chronic kidney disease is a serious clinical problem that comprises imprecision, and the use of fuzzy inference system is suggested to overcome this issue. The proposed FES is implemented in the MATLAB.

中文翻译：

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基于新型模糊逻辑的慢性肾脏病诊断专家系统

慢性肾脏病是威胁生命的并发症。初步诊断和主动控制可避免其进展。为了延长患者的寿命，有必要在早期发现这种疾病。在这篇研究论文中，提出了一种用于识别慢性肾脏病当前阶段的模糊专家系统（FES）的设计和开发。所提出的基于模糊规则的专家系统是在临床实践指南，数据库和一组专家的知识的帮助下开发的。它利用诸如肾单位功能，血糖，舒张压，收缩压，年龄，体重指数（BMI）和烟等输入变量。正常性测试适用于不同的输入参数。输入变量，即肾单位功能，血糖，表面分析的结果显示，BMI和BMI对慢性肾脏疾病的影响更大。该系统的输出显示了患者肾脏疾病的当前阶段。在这项研究工作中开发的FES总共进行了80次测试，并将生成的输出与预期输出进行比较。观察到该系统在93.75％的测试中成功。该系统支持医生评估患者中的慢性肾脏疾病。慢性肾脏疾病的检测是一个严重的临床问题，包括不精确性，建议使用模糊推理系统来克服此问题。建议的FES在MATLAB中实现。在这项研究工作中开发的FES总共进行了80次测试，并将生成的输出与预期输出进行比较。观察到该系统在93.75％的测试中成功。该系统支持医生评估患者中的慢性肾脏疾病。慢性肾脏疾病的检测是一个严重的临床问题，包括不精确性，建议使用模糊推理系统来克服此问题。建议的FES在MATLAB中实现。在这项研究工作中开发的FES总共进行了80次测试，并将生成的输出与预期输出进行比较。观察到该系统在93.75％的测试中成功。该系统支持医生评估患者中的慢性肾脏疾病。慢性肾脏疾病的检测是一个严重的临床问题，包括不精确性，建议使用模糊推理系统来克服此问题。建议的FES在MATLAB中实现。并建议使用模糊推理系统来克服这个问题。建议的FES在MATLAB中实现。并建议使用模糊推理系统来克服这个问题。建议的FES在MATLAB中实现。