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首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >Design and implementation of a web-based fuzzy expert system for diagnosing depressive disorder
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Design and implementation of a web-based fuzzy expert system for diagnosing depressive disorder

机译：基于Web的模糊专家系统的设计与实现诊断抑郁症

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摘要

Mental health problems have always existed in human life. However, factors such as lifestyle changes and industrialization affect modern human mental health. A common mental illness is depressive disorder, and a large number of patients are not even aware they have it. Due to the harmful influences of depressive disorder on quality of life, timely and accurate diagnosis is a matter of extreme prominence. The aim of this study is to design a web-based expert system for diagnosing depression using the fuzzy Delphi method by estimating the weights and importance of depression symptoms. Fuzzy Logic is adopted to calculate the level of depression. Two thresholds are obtained, namely lack of depression and severe depression. Finally, the level of depression for each person is estimated by virtue of the calculated value’s proximity to these two opposing points. Java Expert System Shell is used to build the knowledge base. Sensitivity and specificity analysis are performed with 238 participants. The proposed system appears helpful for everyone, from ordinary persons to specialists in medical environments. It can also be useful to train psychology students in the area of diagnostic reasoning.
机译：心理健康问题在人类生活中一直存在。然而，生活方式改变和工业化等因素影响了现代人类心理健康。常见的精神疾病是抑郁症，大量患者甚至都不知道他们拥有它。由于抑郁症对生活质量的有害影响，及时和准确的诊断是极度突出的问题。本研究的目的是通过估计抑郁症状的重量和重要性来设计一种用于诊断抑郁症的基于网络的专家系统。采用模糊逻辑来计算抑郁症水平。获得了两个阈值，即缺乏抑郁和严重抑郁症。最后，通过计算值对这两个相对点的邻近来估计每个人的抑郁水平。 Java Expert System shell用于构建知识库。使用238名参与者进行敏感性和特异性分析。拟议的系统似乎有助于从普通人到医疗环境中的专家。在诊断推理领域培训心理学学生也可有用。

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