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Readability of Arabic Medicine Information Leaflets: A Machine Learning Approach

机译:阿拉伯医学信息传单的可读性:一种机器学习方法

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This paper presents a project that explores the possibility of assessing the readability level of Arabic medicine information leaflets using machine learning techniques. There are a number of popular readability formulas and tools that have been successfully used to assess the readability of health-related information in several languages. However, there is limited work on the readability assessment of health-related information, specifically medicine information leaflets in Arabic. We describe the design of a tool that uses machine learning to assess the readability of medicine information leaflets. We utilize a corpus comprising 1112 medicine information leaflets annotated with three difficulty levels. Based on a study of existing literature, we selected a number of features influencing text difficulty. The tool will help specialized organizations in medicine information leaflets production to produce the leaflets at appropriate level of reading for the majority of leaflets consumers.
机译:本文提出了一个项目,探讨使用机器学习技术评估阿拉伯医学信息单张的可读性水平的可能性。有许多流行的可读性公式和工具已成功用于评估几种语言的健康相关信息的可读性。但是,有关健康相关信息(尤其是阿拉伯语的医学信息传单)的可读性评估的工作有限。我们描述了一种使用机器学习评估药物信息传单的可读性的工具的设计。我们利用一个包含1112个药物信息传单的语料库,并以三个难度级别进行注释。在对现有文献进行研究的基础上,我们选择了许多影响文本难度的功能。该工具将帮助医学信息单张生产的专业组织为大多数单张消费者提供适当阅读水平的单张。

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