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A Context-Aware Middleware for Medical Image Based Reports An approach based on image feature extraction and association rules

机译:基于医学图像的上下文中的中间版本的报告基于图像特征提取和关联规则的方法

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This work proposes a context-aware middleware for medical workflow organization and efficiency improvement. In hospitals, laboratories and teleradiology companies, each physician or technician is specialized in a specific kind of diagnosis or analysis. Therefore, certain types of medical images are often forwarded to a certain physician or a certain group. This forwarding is time consuming. That is, repeatedly deciding who would be the best physician, whether he is available at a certain moment given a certain context is exhaustive and may be very inefficient. Thus, the proposed middleware has the ability to process and collect data from images analyzed by each medical staff. Based on the collected data and current clinical context, the middleware is able to infer who would be the best fit staff to receive a certain incoming medical image.
机译:这项工作提出了用于医疗工作流组织的背景中的中间件和效率改进。在医院,实验室和驻留学企业中,每个医生或技术人员都专门从事特定的诊断或分析。因此,某些类型的医学图像通常转发到某个医生或某个组。这种转发是耗时的。也就是说,反复决定谁将是最好的医生,无论他是否在某个时刻都可以在某种情况下获得令人遗憾的是,可能是非常效率的。因此,所提出的中间件具有处理和收集由每个医务人员分析的图像的数据。基于收集的数据和当前的临床背景,中间件能够推断谁将成为最佳拟合员工,以获得某种传入的医学形象。

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