Duclos Catherine, Cartolano Gian Luigi, Ghez Michael, Venot Alain
Laboratoire d'informatique médicale et de bioinformatique (LIM&BIO), UFR de Santé, Médecine et Biologie Humaine, Paris 13, Bobigny cedex, France.
J Am Med Inform Assoc. 2004 Jul-Aug;11(4):285-93. doi: 10.1197/jamia.M1425. Epub 2004 Apr 2.
The aim of this study was to construct automatically a knowledge base concerning the pharmacodynamic properties of antibiotics and a visualization tool.
The authors studied the various guidelines used to write the pharmacodynamics section of the Summary of Product Characteristics (SPC) for antibiotics and constructed a conceptual model of the information. Particular words, syntagms, and punctuation elements were marked in the SPC texts, and automatic extraction was then used to build a knowledge base. This base was used to create dynamic HTML tables displaying the activity spectra of the antibiotics.
The authors analyzed the performances of automatic extraction (recall and precision).
The conceptual pharmacodynamics model dealt with antibiotics, pathogens, susceptibility tests, and the prevalence of resistance. Automatic extraction had a recall rate of 97.9% and a precision of 96.2%. The tool displaying antibiotic spectra and resistance prevalences used color codes to identify differences in susceptibility.
This tool can provide an overview of the prevalence of resistance as expressed in SPC in primary care settings. Its potential impact should be evaluated.
本研究旨在自动构建一个关于抗生素药效学特性的知识库和一个可视化工具。
作者研究了用于撰写抗生素产品特性总结（SPC）中药效学部分的各种指南，并构建了信息概念模型。在SPC文本中标记了特定的单词、短语和标点元素，然后使用自动提取来构建知识库。该知识库用于创建动态HTML表格，展示抗生素的活性谱。
作者分析了自动提取的性能（召回率和精确率）。
概念性药效学模型涉及抗生素、病原体、药敏试验和耐药率。自动提取的召回率为97.9%，精确率为96.2%。展示抗生素谱和耐药率的工具使用颜色代码来识别药敏差异。
该工具可以概述基层医疗环境中SPC所表达的耐药率情况。其潜在影响应予以评估。
