基于自适应神经模糊推理系统的类风湿关节炎预测

Vishu Madaan, R. Kaur, Prateek Agrawal
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引用次数: 1

摘要

一种不舒服的状态被称为疾病,也被称为疾病或疾病。当像病毒这样最微小的生物进入我们的身体时,它会与身体的细胞发生反应,导致疾病。关节炎的早期预测是很有问题的。它随着年龄的增长而滋长,与大小关节疼痛有关。类风湿关节炎(RA)是一种慢性疾病,它是一种长期的自身免疫性和炎症性疾病,损害许多关节组织。当免疫系统无法区分细胞和组织时,就会发生这种情况。ANFIS模型用于人类RA的预测。本研究提出了一个完整的诊断过程,为类风湿关节炎的诊断提供了一种准确率达93.5%的技术。这一诊断是基于人类生活中的12种RA症状,如年龄、僵硬、关节畸形、ESR、CRP、WBC、尿酸等。并将ANFIS与朴素贝叶斯、Bagging算法和KNN分类器进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rheumatoid Arthritis anticipation using Adaptive Neuro Fuzzy Inference System
A state of discomfort is known as a disease, also termed as illness or sickness. When the tiniest living things like virus enters our body, it reacts with the cells of the body and results an illness. The Arthritis is very problematic to early forecast. It nurtures with the age and related to the large and small joint pain. The Rheumatoid Arthritis (RA) is chronic disease, its long-term auto-immune and inflammatory disease which damages many joints tissues. It occurs when immune system can't distinguish the cells and tissues. The ANFIS model is used for the prediction of the RA in human mortals. A complete process is mentioned in this study, which helps to a technique for the diagnosis of the Rheumatoid Arthritis in human beings with accuracy 93.5%. This diagnosis is made on the bases of 12 symptoms of RA in human lives like age, stiffness, joint deformity, ESR, CRP, WBC, Uric Acid etc. This paper also compares the ANFIS with Naive Bayes, Bagging algorithm and KNN classifiers.
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