自适应神经模糊推理系统在医学领域的应用

Adaptive Neural-Fuzzy Inference System in Medical Practice

医疗领域中存在着很多不确定性,给疾病诊断预测等医疗活动带来了极大困难。模糊神经网络(neural-fuzzy system,NFS)很好地结合了人工神经网络和模糊逻辑的优点,成为一种能从数据中获取知识,并能将知识以模糊规则形式表达的新型人工智能模型。因其强大的分类能力和处理模糊信息能力,模糊神经网络模型被越来越多地应用到医学领域。其中自适应神经模糊推理系统(adaptive neural-fuzzy inference system,ANFIS)是模糊神经网络中应用最多的一种,本文就ANFIS在医学领域的应用进行综述。

There are a great number of uncertainties in medical practice, causing considerable difficulties in medical activities such as diagnosis and prognostic prediction. Neural-fuzzy system（NFS） combines the advantages of artificial neural networks and fuzzy logic very well, and has become a new type of artificial intelligence model which is capable of acquiring knowledge from data and expressing it in the form of fuzzy rules. Because of its strong capability of classification and processing fuzzy information, NFS is more and more used in medical practice. Adaptive neural-fuzzy inference system（ANFIS） is one of the most popular forms of NFS. This review focuses on the use of ANFIS in medical practice.