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首页> 外文期刊>International Journal of Image and Graphics >Decision Support Techniques for Dermatology Using Case-Based Reasoning
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Decision Support Techniques for Dermatology Using Case-Based Reasoning

机译：使用基于案例推理的Dermatology决策支持技术

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摘要

Identification of skin disease has become a challenging task with the origination of various skin diseases. This paper presents a case-based reasoning (CBR) decision support system to enhance dermatological diagnosis for rural and remote communities. In this proposed work, an automated way is introduced to deal with the inconsistency problem in CBRs. This new hybrid architecture is to support the diagnosis in multiple skin diseases. The architecture used case-based reasoning terminology facilitates the medical diagnosis. Case based reasoning system retrieves the data which contains symptoms and treatment plan of the disease from the data repository by the way of matching visual contents of the image, such as shape, texture, and color descriptors. The extracted feature vector is fed into a framework to retrieve the data. The results proved using ROC curve that the proposed architecture yields high contribution to the computer-aided diagnosis of skin lesions. In experimental analysis, the system yields a specificity of 95.25% and a sensitivity of 86.77%. Our empirical evaluation has a superior retrieval and diagnosis performance when compared to the performance of other works.
机译：皮肤病的鉴定已成为各种皮肤病的起源的具有挑战性的任务。本文提出了一种基于案例的推理（CBR）决策支持系统，以增强农村和远程社区的皮肤病学诊断。在这项工作中，引入了一种自动化的方式来处理CBR中的不一致问题。这种新的混合架构是支持多种皮肤病的诊断。使用基于病例的推理术语的建筑促进了医学诊断。基于案例的推理系统通过匹配图像的视觉内容，例如形状，纹理和颜色描述符，从数据存储库中检索包含疾病的症状和治疗计划的数据。提取的特征向量被馈入框架以检索数据。结果采用ROC曲线证明了所提出的建筑对皮肤病变的计算机辅助诊断产生高贡献。在实验分析中，该系统产生95.25％的特异性，灵敏度为86.77％。与其他作品的性能相比，我们的实证评估具有卓越的检索和诊断性能。

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