基于知识的患者影像预取系统:设计、评估与管理。

P J Hu, C P Wei, O R Sheng
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引用次数: 0

摘要

放射科医生的一个基本临床角色是为主治医生提供对个体患者放射图像的解释,这对治疗计划或整体患者管理至关重要。解释新摄放射检查的图像通常需要参考同一患者先前的图像来建立基线,以确认可疑的病理过程或损伤,或评估已确定的病变的进展。这些图像参考对放射科医生的检查阅读至关重要,如果支持不当,可能导致阅读时间延长,报告质量下降和沮丧。为了解决许多医疗机构使用的图像预取方法不足的问题,我们采用基于知识的方法,开发了图像检索专家系统(IRES),该系统结合了相关的医学/放射学知识,并包含放射科医生常用的图像检索启智方法。本文描述了IRES的设计,重点介绍了其初步评估结果,并讨论了在医疗保健组织中管理该技术和类似技术的重要问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A knowledge-based patient image prefetching system: design, evaluation and management.

One fundamental clinical role of radiologists is to provide attending physicians with interpretations of an individual patient's radiological images essential to a treatment plan or overall patient management. Interpreting images from a newly taken radiological examination often requires reference to prior images of the same patient to establish a baseline from which to confirm a suspected pathological process or injury or to evaluate the progression of one that has been identified. Such image references are crucial to the radiologist's examination reading and when inappropriately supported can result in prolonged reading time, decreased report quality, and frustration. To address the problem of inadequate image prefetching methods used by many health care organizations, we took a knowledge-based approach and developed Image Retrieval Expert System (IRES), which incorporates relevant medical/radiological knowledge and contains image retrieval heuristics commonly shared by radiologists. This article describes the design of IRES, highlights its preliminary evaluation results, and discusses issues important for managing this and similar technologies in a health care organization.

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