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Case-based reasoning in Neurological Domain

机译:神经结构域内案例推理

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Case-Based Reasoning (CBR) is an Artificial Intelligence (AI) methodology like rule-based reasoning, neural networks and genetic algorithms. CBR techniques used to dynamically knowledge to discover from previous experiences and advance filtering of variables was the best predictor in comparison to other machine learning methods. This paper presents a Neurology Diagnosis System (NDS) to CBR approach. This system assists to health assistants in the absence of the expert doctors. The work features a compositional adaptation approach, whereby relevant health information elements from the solution component of multiple similar past cases are carefully selected and systematically combined to yield a new personalized health information package. The implementation is a web application developed in the Java programming language using the Spring MVC framework and My-SQL as the database system.
机译:基于案例的推理(CBR)是一种人工智能(AI)方法,如规则的推理,神经网络和遗传算法。用于动态知识的CBR技术从先前的经验中发现并提前过滤变量是与其他机器学习方法相比的最佳预测因子。本文提出了对CBR方法的神经学诊断系统(NDS)。该系统在没有专家医生的情况下协助健康助理。该工作具有组合式适应方法,由此,来自多个类似过去案例的解决方案组件的相关健康信息元素经过仔细选择和系统地组合,以产生新的个性化健康信息包。实现是在Java编程语言中开发的Web应用程序,使用Spring MVC框架和My-SQL作为数据库系统。

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