Hsu William, Taira Ricky K
Medical Imaging Informatics Group, University of California, Los Angeles, CA.
AMIA Annu Symp Proc. 2010 Nov 13;2010:316-20.
Capturing how a patient's medical problems change over time is important for understanding the progression of a disease, its effects, and response to treatment. We describe two prototype tools that are being developed as part of a data processing pipeline for standardizing, structuring, and visualizing problems and findings documented in clinical reports associated with neuro-oncology patients. Given a list of problems and findings identified using a natural language processing (NLP) system, we have created a mapping tool that assigns an observation of a problem to one of nine classes that describe change. The second tool utilizes iconic representations of the nine classes to generate a timeline interface, enabling users to pan, zoom, and filter the data. The result of this preliminary work is an automated approach for understanding and summarizing the evolution of a problem within the patient electronic medical record.
记录患者的医疗问题如何随时间变化，对于理解疾病的进展、其影响以及对治疗的反应至关重要。我们描述了两种正在开发的原型工具，它们是数据处理管道的一部分，用于标准化、结构化和可视化神经肿瘤患者临床报告中记录的问题和发现。给定使用自然语言处理（NLP）系统识别出的问题和发现列表，我们创建了一个映射工具，将问题观察结果分配到描述变化的九个类别之一。第二个工具利用这九个类别的图标表示来生成时间线界面，使用户能够平移、缩放和过滤数据。这项初步工作的结果是一种自动方法，用于理解和总结患者电子病历中问题的演变。
